Farkas Tamás: Családnév-változtatás Magyarországon

La storia della formazione degli insegnanti specializzati per il sostegno degli allievi con disabilità nel nostro Paese ha avuto un andamento sostanzialmente conforme all’evoluzione della normativa e delle scelte politico-culturali che hanno riguardato la scuola italiana (inserimento, integrazione, inclusione). Dalla formazione monovalente biennale si è passati ai corsi polivalenti prima biennali poi annuali – in alcuni casi, come per il ciclo primario, all’interno del Corsi di Laurea in Scienze della Formazione Primaria – per giungere infine ai corsi post lauream. Questi ultimi, giunti al compimento del loro terzo ciclo sembravano, alla luce della riforma introdotta dalla Legge 107/2105, destinati a essere disattivati senza, peraltro, un effettivo riscontro dell’impatto che hanno avuto sul profilo professionale dei docenti che hanno contribuito a formare. L’assenza di una valutazione di tali corsi è un vulnus tipico del nostro sistema formativo e delle azioni promosse dai decisori politici. In tal senso, nella comunità scientifica pedagogica si avverte, e non da oggi, la necessità di avere dati a disposizione per poter contribuire al miglioramento della formazione degli insegnanti, non solo sul piano ideologico (che pure è rilevante per indirizzare la visione del sistema formativo tout court) ma anche su quello della strutturazione di questi percorsi (Cosa serve realmente? Cosa risulta efficace ed efficiente in termini, ad esempio di spendibilità nella pratica quotidiana?, ecc…). Il presente contribuito, intende inserirsi nel solco di questa avvertita necessità portando all’attenzione alcuni dati emersi da una rilevazione condotta al termine del III ciclo del corso di specializzazione svolto presso le sedi convenzionate delle Università di Roma Tre e di Cassino e del Lazio Meridionale

Prediction of Ligand Activity at Subcellular Location

Understanding subcellular distribution and the mechanism of xenobiotics can help in modulating subcellular dysfunction mediated diseases. Therefore, with improved knowledge of how xenobiotics are distributed across subcellular locations and the mechanism for a specific molecule can play a crucial role in assessing drug efficacy and toxicity. Such knowledge would widen therapeutic windows by allowing specific receptors to be targeted efficiently. Based on datasets that provide information on the subcellular locations of proteins and their ligands, we developed machine learning models for 42 subcellular locations. Such models were trained and validated based on the grid search method and best models based on Cohen’s Kappa scores were selected. With the help of the state-of-the-art supercomputing facilities provided by the Texas Advanced Computing Center(TACC), we were able to develop a suite of more than 22300+ machine learning models. These machine learning models were built using 19 different fingerprints-based features for 42 different subcellular locations using 28 different ML classifiers. The web-application is available on an open portal and can be accessed at https://drugdiscovery.utep.edu/subcell/ by anyone in order to perform high-throughput cheminformatics simulations. All the data and models generated from the project are made available as open-source

techno economic analysis of in situ production by electrolysis biomass gasification and delivery systems for hydrogen refuelling stations rome case study

Abstract Starting from the Rome Hydrogen Refuelling Station demand of 65 kg/day, techno-economics of production systems and balance of plant for small scale stations have been analysed. A sensitivity analysis has been done on Levelised Cost of Hydrogen (LCOH) in the range of 0 to 400 kg/day, varying capacity factor and availability hours or travel distance for alkaline electrolysers, biomass gasification and hydrogen delivery. As expected, minimum LCOH for electrolyser and gasifier is found at 400 kg/day and 24 h/day, equal to 12.71 €/kg and 5.99 €/kg however, for operating hours over 12 and 10 h/day the differential cost reaches a plateau (below 5%), for electrolyser and gasifier respectively. For the Rome station design, 160 kWe of electrolysers 24 h/day and 100 kWth gasifier at 8 h/day, LCOH (11.85 €/kg) was calculated considering the modification of the cost structure due to the existing equipment, which is convenient respect the use of a single technology, except for 24 h/day gasification

ETV7 reduces inflammatory responses in breast cancer cells by repressing the TNFR1/NF-κB axis

: The transcription factor ETV7 is an oncoprotein that is up-regulated in all breast cancer (BC) types. We have recently demonstrated that ETV7 promoted breast cancer progression by increasing cancer cell proliferation and stemness and was also involved in the development of chemo- and radio-resistance. However, the roles of ETV7 in breast cancer inflammation have yet to be studied. Gene ontology analysis previously performed on BC cells stably over-expressing ETV7 demonstrated that ETV7 was involved in the suppression of innate immune and inflammatory responses. To better decipher the involvement of ETV7 in these signaling pathways, in this study, we identified TNFRSF1A, encoding for the main receptor of TNF-α, TNFR1, as one of the genes down-regulated by ETV7. We demonstrated that ETV7 directly binds to the intron I of this gene, and we showed that the ETV7-mediated down-regulation of TNFRSF1A reduced the activation of NF-κB signaling. Furthermore, in this study, we unveiled a potential crosstalk between ETV7 and STAT3, another master regulator of inflammation. While it is known that STAT3 directly up-regulates the expression of TNFRSF1A, here we demonstrated that ETV7 reduces the ability of STAT3 to bind to the TNFRSF1A gene via a competitive mechanism, recruiting repressive chromatin remodelers, which results in the repression of its transcription. The inverse correlation between ETV7 and TNFRSF1A was confirmed also in different cohorts of BC patients. These results suggest that ETV7 can reduce the inflammatory responses in breast cancer through the down-regulation of TNFRSF1A

Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer.

Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of \u3e530 PKs have been targeted by FDA-approved medications, and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machine learning to investigate the relations between PKs and cancers, predicting PKs whose inhibition would be efficacious to treat a certain cancer. Our approach represents PKs and cancers as semantically meaningful 100-dimensional vectors based on word and concept neighborhoods in PubMed abstracts. We use information about phase I-IV trials in ClinicalTrials.gov to construct a training set for random forest classification. Our results with historical data show that associations between PKs and specific cancers can be predicted years in advance with good accuracy. Our tool can be used to predict the relevance of inhibiting PKs for specific cancers and to support the design of well-focused clinical trials to discover novel PKIs for cancer therapy

Clinical, pharmacokinetic and pharmacodynamic evaluations of metronomic UFT and cyclophosphamide plus celecoxib in patients with advanced refractory gastrointestinal cancers

Aims. To evaluate UFT and cyclophosphamide (CTX) based metronomic chemotherapy plus celecoxib (CXB) for the treatment of patients with heavily pre-treated advanced gastrointestinal malignancies. Methods. Thirty-eight patients received 500 mg/mq2 CTX i.v bolus on day 1 and, from day 2, 50 mg/day CTX p.o. plus 100 mg/twice a day UFT p.o. and 200 mg/twice a day CXB p.o. Tegafur, 5-FU, 5-FUH2, GHB and uracil pharmacokinetics were assessed. Plasma vascular endothelial growth factor (VEGF), soluble VE-cadherin (sVE-C) and thrombospondin-1 (TSP-1) levels were detected by ELISA and real-time PCR of CD133 gene expression on peripheral blood mononuclear cell was also performed. Results Seventeen patients (45%) obtained stable disease (SD) with a median duration of 5.8 ms (range, 4.2–7.4). Median progression free survival (PFS) and overall survival (OS) were 2.7 ms (95% CI, 1.6–3.9 ms) and 7.1 ms (95% CI, 4.3–9.9 ms), respectively. No toxicities of grade >1 were observed. Pharmacokinetics of 27 patients (13/14, SD/progressive disease, PD) after the first treatment of UFT revealed that 5-FU AUC and Cmax values greater than 1.313 h x microg/ml and 0.501 microg/ml, respectively, were statistically correlated with stabilization of disease and prolonged PFS/OS. VEGF and sVE-C plasma levels were greater in the PD group when compared to SD group. CD133 expression increased only in the PD patients. Conclusion. Metronomic UFT and CTX with CXB in heavily pre-treated gastrointestinal patients were well tolerated and associated with interesting activity. Potential predictive pharmacokinetic parameters and pharmacodynamic biomarkers have been found

How to communicate with families living in complete isolation

The global emergency caused by the SARS-CoV-2 pandemic has suddenly changed how we communicate with families in all the CoViD19 care settings, on account of the need to maintain complete social isolation. Far-reaching mental suffering manifests itself in widespread anxiety. Health workers are isolated from their families, and must manage the consequences of this isolation just like the patients under their care. Patients and their families perceive not only the clinical results but also the personal attitudes, closeness and psychological support from the care teams. This perception of genuine participation by the health worker in the course of the treatment is especially important when a patient dies, and may influence the whole process of grief

The Interplay between CD27dull and CD27bright B Cells Ensures the Flexibility, Stability, and Resilience of Human B Cell Memory

Summary: Memory B cells (MBCs) epitomize the adaptation of the immune system to the environment. We identify two MBC subsets in peripheral blood, CD27dull and CD27bright MBCs, whose frequency changes with age. Heavy chain variable region (VH) usage, somatic mutation frequency replacement-to-silent ratio, and CDR3 property changes, reflecting consecutive selection of highly antigen-specific, low cross-reactive antibody variants, all demonstrate that CD27dull and CD27bright MBCs represent sequential MBC developmental stages, and stringent antigen-driven pressure selects CD27dull into the CD27bright MBC pool. Dynamics of human MBCs are exploited in pregnancy, when 50% of maternal MBCs are lost and CD27dull MBCs transit to the more differentiated CD27bright stage. In the postpartum period, the maternal MBC pool is replenished by the expansion of persistent CD27dull clones. Thus, the stability and flexibility of human B cell memory is ensured by CD27dull MBCs that expand and differentiate in response to change. : Grimsholm et al. show that CD27dull and CD27bright represent sequential MBC developmental stages. T cell- and germinal center (GC)-independent CD27dull MBCs are the plastic source of strongly selected and GC-dependent CD27bright MBCs. CD27dull MBCs, able to expand and differentiate in response to change, ensure stability and flexibility of human B cell memory. Keywords: memory B cells, pregnancy, immunological memory, CD27, VH repertoire, immunodeficiency, aging, spleen, vaccine, germinal cente

Search for the Higgs boson in events with missing transverse energy and b quark jets produced in proton-antiproton collisions at s**(1/2)=1.96 TeV

We search for the standard model Higgs boson produced in association with an electroweak vector boson in events with no identified charged leptons, large imbalance in transverse momentum, and two jets where at least one contains a secondary vertex consistent with the decay of b hadrons. We use ~1 fb-1 integrated luminosity of proton-antiproton collisions at s**(1/2)=1.96 TeV recorded by the CDF II experiment at the Tevatron. We find 268 (16) single (double) b-tagged candidate events, where 248 +/- 43 (14.4 +/- 2.7) are expected from standard model background processes. We place 95% confidence level upper limits on the Higgs boson production cross section for several Higgs boson masses ranging from 110 GeV/c2 to 140 GeV/c2. For a mass of 115 GeV/c2 the observed (expected) limit is 20.4 (14.2) times the standard model prediction.Comment: 8 pages, 2 figures, submitted to Phys. Rev. Let