Impact of Immune Parameters and Immune Dysfunctions on the Prognosis of Patients with Chronic Lymphocytic Leukemia.

Chronic lymphocytic leukemia (CLL) is characterized by a wide spectrum of immune alterations, affecting both the innate and adaptive immunity. These immune dysfunctions strongly impact the immune surveillance, facilitate tumor progression and eventually affect the disease course. Quantitative and functional alterations involving conventional T cells, γδ T cells, regulatory T cells, NK and NKT cells, and myeloid cells, together with hypogammaglobulinemia, aberrations in the complement pathways and altered cytokine signature have been reported in patients with CLL. Some of these immune parameters have been shown to associate with other CLL-related characteristics with a known prognostic relevance or to correlate with disease prognosis. Also, in CLL, the complex immune response dysfunctions eventually translate in clinical manifestations, including autoimmune phenomena, increased risk of infections and second malignancies. These clinical issues are overall the most common complications that affect the course and management of CLL, and they also may impact overall disease prognosis.

Extracellular Vesicles as Biomarkers of Acute Graft-vs.-Host Disease After Haploidentical Stem Cell Transplantation and Post-Transplant Cyclophosphamide.

Even with high-dose post-transplant cyclophosphamide (PT-Cy) which was initially introduced for graft-versus-host disease (GvHD) prevention in the setting of HLA-haploidentical transplantation, both acute and chronic GvHDs remain a major clinical challenge. Despite improvements in the understanding of the pathogenesis of both acute and chronic GvHDs, reliable biomarkers that predict their onset have yet to be identified. We recently studied the potential correlation between extracellular vesicles (EVs) and the onset of acute (a)GvHD in transplant recipients from related and unrelated donors. In the present study, we further investigated the role of the expression profile of membrane proteins and their microRNA (miRNA) cargo (miRNA100, miRNA155, and miRNA194) in predicting the onset of aGvHD in haploidentical transplant recipients with PT-Cy. Thirty-two consecutive patients were included. We evaluated the expression profile of EVs, by flow cytometry, and their miRNA cargo, by real-time PCR, at baseline, prior, and at different time points following transplant. Using logistic regression and Cox proportional hazard models, a significant association between expression profiles of antigens such as CD146, CD31, CD140a, CD120a, CD26, CD144, and CD30 on EVs, and their miRNA cargo with the onset of aGvHD was observed. Moreover, we also investigated a potential correlation between EV expression profile and cargo with plasma biomarkers (e.g., ST2, sTNFR1, and REG3a) that had been associated with aGVHD previously. This analysis showed that the combination of CD146, sTNFR1, and miR100 or miR194 strongly correlated with the onset of aGvHD (AUROC >0.975). A large prospective multicenter study is currently in progress to validate our findings.

Radio Frequency IDentification for Meat Supply-Chain Digitalisation.

Abstract Digitalised supply-chain traceability systems can offer wide prospects both for improving safety as well as enhancing perceived quality [...].

UAV and Machine Learning Based Refinement of a Satellite-Driven Vegetation Index for Precision Agriculture.

Precision agriculture is considered to be a fundamental approach in pursuing a low-input, high-efficiency, and sustainable kind of agriculture when performing site-specific management practices. To achieve this objective, a reliable and updated description of the local status of crops is required. Remote sensing, and in particular satellite-based imagery, proved to be a valuable tool in crop mapping, monitoring, and diseases assessment. However, freely available satellite imagery with low or moderate resolutions showed some limits in specific agricultural applications, e.g., where crops are grown by rows. Indeed, in this framework, the satellite's output could be biased by intra-row covering, giving inaccurate information about crop status. This paper presents a novel satellite imagery refinement framework, based on a deep learning technique which exploits information properly derived from high resolution images acquired by unmanned aerial vehicle (UAV) airborne multispectral sensors. To train the convolutional neural network, only a single UAV-driven dataset is required, making the proposed approach simple and cost-effective. A vineyard in Serralunga d'Alba (Northern Italy) was chosen as a case study for validation purposes. Refined satellite-driven normalized difference vegetation index (NDVI) maps, acquired in four different periods during the vine growing season, were shown to better describe crop status with respect to raw datasets by correlation analysis and ANOVA. In addition, using a K-means based classifier, 3-class vineyard vigor maps were profitably derived from the NDVI maps, which are a valuable tool for growers.

TCR density in early iNKT cell precursors regulates agonist selection and subset differentiation in mice.

It is established that iNKT cells are a cell type that require strong TCR signal for their proper development and represent a model for thymic agonist selection. The nature of the signal perceived by iNKT cells promoting their specification is not well understood. To address this question, we analyzed iNKT cell development in relevant TCR Vα14-Jα18 alpha chain transgenic mice (Vα14Tg). In CD4-Vα14Tg mice, where the transgene is driven by CD4 promoter, we identified a block in iNKT cell development at early developmental stages due to a reduced expression of key transcription factors accompanied with a reduced TCR expression levels. This indicates that TCR signal strength control iNKT cell differentiation. Importantly, we found in WT mice that early precursors of iNKT cells express higher TCR levels compared to positively selected precursors of mainstream T cells showing that TCR levels could contribute to the strength of iNKT cell TCR signaling. Overall, our study highlights TCR signal strength associated with a higher TCR density as an important regulator of iNKT cell lineage specification.