Substantial impact of mobility restrictions on reducing COVID-19 incidence in Italy in 2020

Italy was the first country after China to be severely affected by the COVID-19 pandemic, in early 2020. The country responded swiftly to the outbreak with a nationwide two-step lockdown, the first one light, and the second one tight. By analysing 2020 national mobile phone movements, we assessed how lockdown compliance influenced its efficacy

Clinicopathological and Molecular Findings in a Case of Canine Anaplasma phagocytophilum

A documented case of canine granulocytic anaplasmosis coupled with the molecular characterization of the etiological agent is reported for the first time in Northern Italy. The patient showed nonspecific clinical signs such as fever and weight loss. The most relevant clinicopathological findings were thrombocytopenia, hypoalbuminemia, and normal azotemic proteinuria consistent with glomerular diseases. Blood smear examination revealed the presence of intracytoplasmatic inclusions in neutrophils associated with high positive serology for Anaplasma phagocytophilum. PCR analysis and sequencing of the amplicon confirm serological diagnosis of A. phagocytophilum. Phylogenetic analysis evidenced that the detected bacterial strain belongs to the A. phagocytophilum Europe 1 lineage. Data indicates that A. phagocytophilum circulates in natural environments of Emilia-Romagna region (Northern Italy) and its prevalence in dogs could be underestimated because the clinical signs are frequently nonspecific and a certain diagnosis requires the combination of clinicopathological and molecular assays. Pets living in this area should be regularly monitored and treated for ectoparasites to minimize health risks for humans and pets. Also, surveillance of A. phagocytophilum should be improved in Northern Italy and canine anaplasmosis should be considered in differential diagnosis of persistent proteinuria

Targeted quantitative metabolic profiling of brain-derived cell cultures by semi-automated MEPS and LC-MS/MS

The accurate characterisation of metabolic profiles is an important prerequisite to determine the rate and the efficiency of the metabolic pathways taking place in the cells. Changes in the balance of metabolites involved in vital processes such as glycolysis, tricarboxylic acid (TCA) cycle, oxidative phosphorylation (OXPHOS), as well as in the biochemical pathways related to amino acids, lipids, nucleotides, and their precursors reflect the physiological condition of the cells and may contribute to the development of various human diseases. The feasible and reliable measurement of a wide array of metabolites and biomarkers possesses great potential to elucidate physiological and pathological mechanisms, aid preclinical drug development and highlight potential therapeutic targets. An effective, straightforward, sensitive, and selective liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach was developed for the simultaneous quali-quantitative analysis of 41 compounds in both cell pellet and cell growth medium obtained from brain-derived cell cultures. Sample pretreatment miniaturisation was achieved thanks to the development and optimisation of an original extraction/purification approach based on digitally programmed microextraction by packed sorbent (eVol®-MEPS). MEPS allows satisfactory and reproducible clean-up and preconcentration of both low-volume homogenate cell pellet lysate and cell growth medium with advantages including, but not limited to, minimal sample handling and method sustainability in terms of sample, solvents, and energy consumption. The MEPS-LC-MS/MS method showed good sensitivity, selectivity, linearity, and precision. As a proof of concept, the developed method was successfully applied to the analysis of both cell pellet and cell growth medium obtained from a line of mouse immortalised oligodendrocyte precursor cells (OPCs; Oli-neu cell line), leading to the unambiguous determination of all the considered target analytes. This method is thus expected to be suitable for targeted, quantitative metabolic profiling in most brain cell models, thus allowing accurate investigations on the biochemical pathways that can be altered in central nervous system (CNS) neuropathologies, including e.g., mitochondrial respiration and glycolysis, or use of specific nutrients for growth and proliferation, or lipid, amino acid and nucleotide metabolism

Inhibition of fatty acid synthesis induces differentiation and reduces tumor burden in childhood neuroblastoma

Many metabolic pathways, including lipid metabolism, are rewired in tumors tosupport energy and biomass production and to allow adaptation to stressful en-vironments. Neuroblastoma is the second deadliest solid tumor in children. Ge-netic aberrations, as the amplification of theMYCN-oncogene, correlate stronglywith disease progression. Yet, there are only a few molecular targets successfullyexploited in the clinic. Here we show that inhibition of fatty acid synthesis led toincreased neural differentiation and reduced tumor burden in neuroblastomaxenograft experiments independently ofMYCN-status. This was accompaniedby reduced levels of the MYCN or c-MYC oncoproteins and activation of ERKsignaling. Importantly, the expression levels of genes involved inde novofattyacid synthesis showed prognostic value for neuroblastoma patients. Our findingsdemonstrate that inhibition ofde novofatty acid synthesis is a promising pharma-cological intervention strategy for the treatment of neuroblastoma indepen-dently ofMYCN-status

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Decoding Agc1 deficiency: bioinformatics approaches to unveil the functional implications of Slc25a12 on the transcriptome and epigenome

In the brain, mutations in SLC25A12 gene encoding AGC1 cause an ultra-rare genetic disease reported as a developmental and epileptic encephalopathy associated with global cerebral hypomyelination. Symptoms of the disease include diffused hypomyelination, arrested psychomotor development, severe hypotonia, seizures and are common to other neurological and developmental disorders. Amongst the biological components believed to be most affected by AGC1 deficiency are oligodendrocytes, glial cells responsible for myelination. Recent studies (Poeta et al, 2022) have also shown how altered levels of transcription factors and epigenetic modifications greatly affect proliferation and differentiation in oligodendrocyte precursor cells (OPCs). In this study we explore the transcriptomic landscape of Agc1 in two different system models: OPCs silenced for Agc1 and iPSCs from human patients differentiated to neural progenitors. Analyses range from differential expression analysis, alternative splicing, master regulator analysis. ATAC-seq results on OPCs were integrated with results from RNA-Seq to assess the activity of a TF based on the accessibility data from its putative targets, which allows to integrate RNA-Seq data to infer their role as either activators or repressors. All the findings for this model were also integrated with early data from iPSCs RNA-seq results, looking for possible commonalities between the two different system models, among which we find a downregulation in genes encoding for SREBP, a transcription factor regulating fatty acids biosynthesis, a key process for myelination which could explain the hypomyelinated state of patients. We also find that in both systems cells tend to form more neurites, likely losing their ability to differentiate, considering their progenitor state. We also report several alterations in the chromatin state of cells lacking Agc1, which confirms the hypothesis for which Agc1 is not a disease restricted only to metabolic alterations in the cells, but there is a profound shift of the regulatory state of these cells

Leggere le trasformazioni del paesaggio a partire dal riconoscimento del valore delle permanenze.

This research brings some reflections developed as part of the Integrated Area Project called "Enhancement of the territory of the Prati Stabili of the Mincio Valley". The landscape reading starts from the consideration that the observation of the landscape must be able to recognize its complexity and stratification. In our experience, a double interest has emerged: reading the consistency of the relationships that distinguish the anthropized territorial elements and decoding the cultural meanings that can be traced in the various territorial uses and at the different historical thresholds. This research activity was based on the identification, and subsequent evaluation, of the permanences and transformations and on the study of the cultural and perceptive dimension. The reading of the permanences allows to recognize the links with the past, those relations necessary to define a territorial project able to enhance stratified elements which are fundamental for identity and culture

Profilazione e pubblicità comportamentale

Balboni, P. (2013) Profilazione e pubblicità comportamentale. In N. Bernardi, M. Perego, M. Polacchini & M. Soffientini (eds.), Privacy Officer. La figura chiave della data protection europea, IPSOA, Milan, 148 – 15

Prediction of Metabolic Profiles from Transcriptomics Data in Human Cancer Cell Lines

The Metabolome and Transcriptome are mutually communicating within cancer cells, and this interplay is translated into the existence of quantifiable correlation structures between gene expression and metabolite abundance levels. Studying these correlations could provide a novel venue of understanding cancer and the discovery of novel biomarkers and pharmacological strategies, as well as laying the foundation for the prediction of metabolite quantities by leveraging information from the more widespread transcriptomics data. In the current paper, we investigate the correlation between gene expression and metabolite levels in the Cancer Cell Line Encyclopedia dataset, building a direct correlation network between the two molecular ensembles. We show that a metabolite/transcript correlation network can be used to predict metabolite levels in different samples and datasets, such as the NCI-60 cancer cell line dataset, both on a sample-by-sample basis and in differential contrasts. We also show that metabolite levels can be predicted in principle on any sample and dataset for which transcriptomics data are available, such as the Cancer Genome Atlas (TCGA)