Analisi dell'integrazione delle tecnologie blockchain e Internet of Things

La tecnologia blockchain è emersa come un'innovazione dalle potenzialità di segnare un importante svolta nel modo di condividere le informazioni. Il punto di forza di tale tecnologia è quello di offrire soluzioni di consenso in modo da garantire la fiducia in ambienti distribuiti. Un'altra importante caratteristica della blockchain è quella di risolvere i problemi di sicurezza i quali rappresentano uno degli aspetti cruciali nell’IoT. Il lavoro svolto in questa tesi mira ad offrire una panoramica dettagliata delle due tecnologie in modo da capire quali siano i punti dove l’integrazione di esse possa essere più fattibile rispetto ad altri. Tuttavia, nonostante vi siano ancora molte sfide da affrontare, si può concludere che la combinazione delle due tecnologie possa fungere da apriporta a nuove opportunità di business, difficilmente immaginabili con gli strumenti di cui si disponeva qualche anno fa

Detection of the expression and Cdt activity of CdtB from 15 <i>H. parasuis</i> reference strains and 109 <i>H. parasuis</i> clinical isolates.

<p>(A), Whole cell proteins of 15 <i>H. parasuis</i> reference strains were applied to western bolt and detected by anti-CdtB specific antibody.1–15 represents 15 <i>H. parasuis</i> reference strains, 0165 strain was used as positive control. (B), Cells were incubated with medium alone (negative control), 50 µg/ml CdtABC^WT or 200 µg/ml whole cell proteins of 15 <i>H. parasuis</i> reference strains for 24 h, stained with propidium iodide, and analyzed for cell cycle distribution by flow cytometry as described above. (C), the whole cell proteins of 109 clinical isolates were applied to western bolt and detected by anti-CdtB specific antibody. M, marker; C, 0165 strain was used as positive control.</p

Positive-specific iterated BLAST alignment of CdtB and assessment of CdtB mutants for their ability to induce G₂ arrest.

<p>(A), The alignment is taken directly from the final iteration. M, metal ion-binding residues; C, catalytic residues; asterisk, DNA residues. (B), PAM cells were exposed to medium alone (Negative control) or 200 µl CdtA and CdtC (50 µg/ml) in the presence of CdtB^WT (50 µg/ml) (Positive control) or CdtB^R118A, CdtB^H161Q, CdtB^D235A, CdtB^D267A or CdtB^H268Q (50 µg/ml). Cells were analyzed for cell cycle distribution 24 h after exposure to toxin subunits using flow cytometric analysis of propidium iodide fluorescence. The numbers in each panel represent the percentages of cells in G₂/M. Results are representative of three experiments.</p

Structural alignment and assessment of CRAC site mutants in CdtC subunits for their ability to induce G₂ arrest.

<p>(A), structural alignment of CRAC site in <i>H. parasuis</i>, CdtC in <i>A. actinomycetemcomitans</i> and the classical CRAC sites. (B), assessment of CRAC site mutants for their ability to induce G₂ arrest. The cells were incubated with medium alone, 50 µg/ml CdtABC^WT, 50 µg/ml CdtABC^V77Y or 50 µg/ml CdtABC^V77A for 24 h, stained with propidium iodide, and analyzed for cell cycle distribution by flow cytometry as described above.</p

Effect of various combinations of the Cdt subunits for their ability to induce G₂ arrest and effect of CdtA and CdtC on CdtB-induced G₂ arrest.

<p>The cells were analyzed for cell cycle distribution by treated with Cdt proteins alone or in various combinations (as indicated) following staining with propidium iodide. (A), PAM cell; (B), PK-15 cell; (C) Jurkat cell or (D) PAM cells were exposed to 200 µl CdtB alone (50 µg/ml) or in the presence of CdtA (50 µg/ml) or CdtC (50 µg/ml). The cells were analyzed for cell cycle distribution by flow cytometry based upon propidium iodide fluorescence. The data represent the mean ± SEM of three experiments; at least 20,000 cells were analyzed per sample.</p

Phylogenetic analysis of two Cdts in the strain SH0165 and 29755 on the basis of the ClustalW method in Lasergene software (DNASTAR).

<p>(A), CdtA; (B), CdtB; (C), CdtC; (D), the relationship between CdtB in strain SH0165 and 29755 and that in the other bacterium species produced CdtB, on the basis of the ClustalW method.</p

Clustering and characterization of the differential expression of genes.

<p>(A) SE38 group vs. PBS group. S95H_NS, S50H_NS and S96_H_NS belong to SE38 group; S32H_NS, S32H_2_NS and S71H_NS belong to PBS group. DE genes that showed clear functional annotation at 4 dpi between the SE38 and PBS groups were selected for cluster analysis as described in methods. At 4 dpi, a set of 262 genes were upregulated and the remaining 132 genes were downregulated. (B) G4T10 group vs. PBS group. S98H_NS, SR_1_H_NS and SR_2_H_NS belong to G4T10 group; S32H_NS, S32H_2_NS and S71H_NS belong to PBS group. Each row represents a separate gene and each column represents a separate piglet. Red indicates the increased gene expression levels; green denotes the decreased levels compared with normal samples.</p

Transcription analysis of the responses of porcine heart to <i>Erysipelothrix rhusiopathiae</i>

<div><p><i>Erysipelothrix rhusiopathiae</i> (<i>E</i>. <i>rhusiopathiae</i>) is the causative agent of swine erysipelas. This microbe has caused great economic losses in China and in other countries. In this study, high-throughput cDNA microarray assays were employed to evaluate the host responses of porcine heart to <i>E</i>. <i>rhusiopathiae</i> and to gain additional insights into its pathogenesis. A total of 394 DE transcripts were detected in the active virulent <i>E</i>. <i>rhusiopathiae</i> infection group compared with the PBS group at 4 days post-infection. Moreover, 262 transcripts were upregulated and 132 transcripts were downregulated. Differentially expressed genes were involved in many vital functional classes, including inflammatory and immune responses, signal transduction, apoptosis, transport, protein phosphorylation and dephosphorylation, metabolic processes, chemotaxis, cell adhesion, and innate immune responses. Pathway analysis demonstrated that the most significant pathways were Chemokine signaling pathway, NF-kappa B signaling pathway, TLR pathway, CAMs, systemic lupus erythematosus, chemokine signaling pathway, Cytokine–cytokine receptor interaction, PI3K-Akt signaling pathway, Phagosome, HTLV-I infection, Measles, Rheumatoid arthritis and natural-killer-cell-mediated cytotoxicity. The reliability of our microarray data was verified by performing quantitative real-time PCR. This study is the first to document the response of piglet heart to <i>E</i>. <i>rhusiopathiae</i> infection. The observed gene expression profile could help screen potential host agents that can reduce the prevalence of <i>E</i>. <i>rhusiopathiae</i>. The profile might also provide insights into the underlying pathological changes that occur in pigs infected with <i>E</i>. <i>rhusiopathiae</i>.</p></div

Representative histopathological photomicrograph of heart lesions in pigs infected with <i>E</i>. <i>rhusiopathiae</i> strain SE38, G4T10 and control.

<p>(A) Heart of a SE38-infected pig with endocarditis and neutrophil infiltration. (B) Thrombogenesis, myocardial necrosis, and inflammatory cell infiltration. (C) Heart of a G4T10-infected pig at 200 and 50μm. (D) PBS control at 200 and 50 μm.</p

Results of culture and PCR analysis for three pigs challenged with <i>E</i>. <i>rhusiopathiae</i> presented as the number of positive pigs/total pig samples.

<p>Results of culture and PCR analysis for three pigs challenged with <i>E</i>. <i>rhusiopathiae</i> presented as the number of positive pigs/total pig samples.</p