130,402 research outputs found
Advanced IoT Edge Architecture for Smart City
No full textIn the last few years, terms like Internet of Things, Cloud Computing and Edge Computing have captured a lot of attention from both scientific and industrial perspectives. They are independent but closely related concepts, and their use extends into several scenarios, such as Smart Agriculture, Smart Home, autonomous vehicles, and Smart City, to name but a few. Among the Smart City solutions, Smart Parking aims to solve the problem of parking space and parking management in big cities, since the search for free parking spaces brings along a serious cost, air pollution and stress issues. The objective of this article is to propose an Edge Computing architecture tailored for Smart Parking solutions, addressing the challenges of real-time data processing and efficient parking management. This architecture integrates a Deep Learning solution based on Gated Recurrent Units (GRU) to accurately forecast the number of available and occupied parking spaces
UNCOVERING IMMUNE EVASION MECHANISMS FOR THE PROGNOSIS AND THERAPY OF ENDOMETRIAL AND OVARIAN CANCERS
No full textGynecologic malignancies are a heterogeneous group of solid tumors which include endometrial cancer (EC) and ovarian cancer (OC). EC is the most common gynecological neoplasm and the only gynecologic cancer with increasing incidence and mortality. It is generally diagnosed at an early stage and is well managed with surgery, radiation, and/or chemotherapy. However, EC patients with advanced/recurrent disease have poor outcomes and respond poorly to current management treatments. On the other hand, OC is a devastating disease since the majority of patients, when first diagnosed, are at advanced clinical stages (III/IV). Furthermore, relapse occurs in more than 70% of patients and the 5-year survival rate is lower than 40%. Thus, it is important the development of novel therapeutic approaches. In this context, remarkable progresses have been made in immunotherapy. In fact, several preclinical and clinical studies are ongoing with immunotherapeutic strategies combined or not with classic treatments. To date, the efficacy is not satisfactory, thus a detailed understanding of the biology and interactions between cancer and the immune system is essential for the recognition and development of potential new immunotherapeutic strategies and targets as well as the optimization of existing immunotherapies. Therefore, the aim of this thesis was to characterize the molecular profile, frequency, phenotype and function of immune cells in EC and OC patients.
In particular, considering that the presence of activated tissue-resident gamma delta (γδ) T cells, recognized for their favorable response in various human malignancies, has been associated with a beneficial response to immunotherapies, and that their role in EC progression has not been elucidated yet, we performed a characterization of γδ T cells in EC. Flow cytometry analysis reveals that Vδ1 is the primary subset of γδ T cells infiltrating EC lesions in both early and advanced stages. Upon in vitro stimulation, these cells maintain their functional activity by producing cytokines, such as interferon (IFN)-γ and tumor necrosis factor (TNF)-α. However, within the tumor, they exhibit increased expression of PD-1, compared to their blood-matched circulating counterparts. Single-cell RNA-sequencing (scRNA-seq) analysis confirmed the upregulation of PD-1 expression in γδ T cells, exhibiting a progressive increase from peritumor to tumor specimens, in contrast to healthy tissue. Crucially, tumor-infiltrating Vδ1 T cells expressing PD-1 retain their immune competence, which can be enhanced by PD-1 blockade. Indeed, their cytotoxic response against autologous tumor cell targets significantly increases in the presence of the specific blocking anti-PD-1 monoclonal antibody compared to controls. Moreover, scRNA-seq analysis associated the presence and the specific activation of Vδ1 T cells with the response to anti-PD-1 therapy. These data not only emphasize the specific anti-tumor response of Vδ1 T cells in EC but also indicate the feasibility of targeting γδ T cells to enhance current immunotherapeutic strategies.
As few studies have been conducted on the early stages (stage I) of OC due to the difficulty in diagnosing this disease, we performed a deep characterization through scRNA-seq of stage I high-grade serous ovarian cancer (HGSOC) tumor microenvironment (TME), the most common subtype of OC, to assess the impact of the TME in OC progression and to identify potential immunotherapeutic targets. Within the HGSOC lesions we detected high enrichment of CD4 regulatory T cells (Tregs) that displayed a spectrum of states linked to their naïve, effector, proliferating and destabilized transcriptomic profiles. The presence of FOXP3+ Tregs associates with a permissive, immune-suppressive TME, characterized by the prevalence of CD4 Th2 cells, exhaustion of cytotoxic CD8 T cells, and pro-tumoral states of natural killer (NK) cells and tumor-associated macrophages (TAMs). Cell-to-cell communication analysis predicted multiple molecular mechanisms underlying Treg inhibition of T and myeloid immune responses, along with the establishment of reciprocal interactions between Tregs and tumor cells, promoting tumor progression. Trajectory analysis revealed two differentiation paths for Tregs, both leading to immunosuppressive Treg profiles. While the FOXP3high profile converges with proliferating Tregs, the second path of cytotoxic FOXP3+ Tregs converged with FOXP3-KLRB1+ ex-Tregs, distinguished for their anti-tumoral CXCL13+IFNG+ transcriptomic profile. These findings highlight the pivotal role of Tregs in the early establishment of the immunosuppressive TME conducive to HGSOC, also highlighting the potential of manipulating Treg cell fate and their de-stabilization as a promising target for therapeutic interventions
NKG2A Immune Checkpoint in Vδ2 T Cells: Emerging Application in Cancer Immunotherapy
No full textImmune regulation has revolutionized cancer treatment with the introduction of T-cell-targeted immune checkpoint inhibitors (ICIs). This successful immunotherapy has led to a more complete view of cancer that now considers not only the cancer cells to be targeted and destroyed but also the immune environment of the cancer cells. Current challenges associated with the enhancement of ICI effects are increasing the fraction of responding patients through personalized combinations of multiple ICIs and overcoming acquired resistance. This requires a complete overview of the anti-tumor immune response, which depends on a complex interplay between innate and adaptive immune cells with the tumor microenvironment. The NKG2A was revealed to be a key immune checkpoint for both Natural Killer (NK) cells and T cells. Monalizumab, a humanized anti-NKG2A antibody, enhances NK cell activity against various tumor cells and rescues CD8 αβ T cell function in combination with PD-1/PD-L1 blockade. In this review, we discuss the potential for targeting NKG2A expressed on tumor-sensing human γδ T cells, mostly on the specific Vδ2 T cell subset, in order to emphasize its importance and potential in the development of new ICI-based therapeutic approaches
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Validation of the Pediatric Evaluation of Disability Inventory in an Italian Population with Autism Spectrum Disorder: a Cross-Sectional Study
No full textObjective To measure psychometric properties of the Italian version of the Pediatric Evaluation of Disability Inventory (PEDI-I) in a population with Autism Spectrum Disorder (ASD). Methods The PEDI-I was administered to different children with ASD. The internal consistency was examined by using Cronbach’s Alpha, while the intraclass correlation coefficient (ICC) was used to investigate both inter-observer and intra-observer reproducibility. Its concurrent validity was evaluated with the Italian version of the Barthel Index. Results The PEDI-I was administered to 60 children with a diagnosis of ASD. Cronbach’s Alpha showed statistically significant values (.885-.965). Inter-observer and intra-observer investigations confirm the reproducibility of the scale with a range of high and very high parameters. The Pearson Correlation Coefficient with the Barthel Index showed significant data for all PEDI-I subscales with a p<0.01. Conclusions The PEDI-I showed good psychometric properties and it is possible to confirm its validity and reliability in ASD population. However, for better understanding of how PEDI-I works in clinical practice, further researches are recommende
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Tumor microenvironment in primary liver tumors : A challenging role of natural killer cells
No full textIn the last years, several studies have been focused on elucidate the role of tumor microenvironment (TME) in cancer development and progression. Within TME, cells from adaptive and innate immune system are one of the main abundant components. The dynamic interactions between immune and cancer cells lead to the activation of complex molecular mechanisms that sustain tumor growth. This important cross-talk has been elucidate for several kind of tumors and occurs also in patients with liver cancer, such as hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). Liver is well-known to be an important immunological organ with unique microenvironment. Here, in normal conditions, the rich immune-infiltrating cells cooperate with non-parenchymal cells, such as liver sinusoidal endothelial cells and Kupffer cells, favoring self-tolerance against gut antigens. The presence of underling liver immunosuppressive microenvironment highlights the importance to dissect the interaction between HCC and iCCA cells with immune infiltrating cells, in order to understand how this cross-talk promotes tumor growth. Deeper attention is, in fact, focused on immune-based therapy for these tumors, as promising approach to counteract the intrinsic anti-tumor activity of this microenvironment. In this review, we will examine the key pathways underlying TME cell-cell communications, with deeper focus on the role of natural killer cells in primary liver tumors, such as HCC and iCCA, as new opportunities for immune-based therapeutic strategies
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