Comunicare e promuovere. Analisi e verifica progettuale per la definizione di linee guida e di strumenti per la valorizzazione dei marchi storici

La ricerca ha l'obiettivo di avviare uno studio sul patrimonio dei marchi d'impresa storici torinesi, per definire criteri, strumenti ed esiti progettuali finalizzati alla loro promozione e valorizzazione anche in un'ottica d'imprenditorialità. Lo scopo è studiare l'impatto che tale azione può avere sul comparto economico con particolare attenzione agli "aspetti relazionali" tra i diversi attori e la promozione della cultura storica e del valore dei marchi per le nuove generazioni. Dall'insieme di 25.000 marchi d'impresa, depositati dal 1927 al 1970, i ricercatori hanno avviato un progetto impiegando gli strumenti organizzativi, creativi e visivi tipici della big data analysis, comprendenti una ricerca quantitativa su categorie merceologiche definite; l'implementazione di un metodo di elaborazione; il filtraggio dei dati e la selezione ai fini della visualizzazione; un'analisi tassonomica sulla figuratività per ipotizzare una classificazione basata su tag utili alle ricerche archivistiche e allo storytelling d'archivio

Aurora Kinases: New Molecular Targets for the Therapy of Aggressive Thyroid Cancers

Epithelial thyroid carcinomas (TC) account for more than 90% of all endocrine malignancies and represent one of the most frequent cancers in women. They include the well-differentiated TC (DTC), comprising the papillary (PTC) and follicular (FTC) histotypes, the poorly differentiated (PDTC), and the undifferentiated or anaplastic TC (ATC). Both PDTC and ATC are aggressive human neoplasms with a dire prognosis due to the absence of effective therapies, which makes mandatory the identification of novel therapeutic strategies. Intrinsic chromosomal instability (CIN, an increased rate of gain or losses of chromosomes during cell division) is a common feature of solid tumors and represents a major driving force in thyroid cancer progression, thought to be responsible for the acquisition by malignant cells of novel functional capabilities. Different mitotic kinases, whose expression or function has been found altered in human cancer tissues, are major drivers of thyroid tumor aneuploidy. Among these are the three members of the Aurora family (Aurora-A, Aurora-B and Aurora-C), serine/threonine kinases that regulate multiple aspects of chromosome segregation and cytokinesis. Over the last few years, several small molecule inhibitors targeting Aurora kinases were developed with promising antitumor effects in preclinical and clinical studies against different human cancers, including TC. Here, we will focus on the Aurora mitotic functions in normal cells; we shall then describe the main implications of their overexpression in the onset of genetic instability and aneuploidy. We will finally describe the consequences of Aurora kinase inhibition on TC cell growth and tumorigenicity

A CASE-CONTROL STUDY OF NEUROTOXIC METALS IN CEREBROSPINAL FLUID AND RISK OF AMYOTROPHIC LATERAL SCLEROSIS

Many studies have investigated the possible relation between exposure to heavy metals and risk of amyotrophic lateral sclerosis (ALS). We aimed at assessing the levels of two neurotoxic metals, cadmium (Cd), lead (Pb) and mercury (Hg) in cerebrospinal fluid (CSF) of ALS patients and hospital controls. CSF heavy metal content was determined using inductively coupled plasma sector field mass spectrometry (ICP-SF-MS) according to methodologies previously established for biological matrices and specifically for CSF. We obtained CSF samples from 38 ALS cases, including 16 men and 22 women, and from 38 hospital-referred subjects undergoing lumbar puncture because of suspected but later unconfirmed neurological disease, with mean age of 55.5 and 52.26 respectively (range 30\u2013 85). Median heavy metal concentrations were higher in ALS cases compared to controls for Pb (155 vs. 132 ng/l) but lower for Cd (36 vs. 72) and Hg (196 vs. 217). In unconditional multiple logistic regression analysis adjusting for age and sex, we found a disease odds ratio (OR) for the middle and the upper exposure tertiles of 0.8 (0.2-2.6) and 1.4 (95% CI 0.5 to 4.2) for Pb, 0.9 (0.3-2.8) and 0.3 (0.1 to 1.0) for Cd, and 12.4 (2.7-57.3) and 3.03 (0.52-17.55) for Hg. We also conducted sensitivity analyses with log transformed values and with winsorized values by setting data exceeding the 95th percentile to the 95th percentile, but the risk estimates did not substantially change. Our results and particularly the lack of dose-response relations give little support for an involvement of these heavy metals in ALS etiology, with the possible exception of Hg. However, caution should be used in the interpretation of these results due to some study limitations, such as the statistical imprecision of the risk estimates, the hospital-based design of the study, and the potential for unmeasured confounding

Driver Stress State Evaluation by Means of Thermal Imaging: A Supervised Machine Learning Approach Based on ECG Signal

Traffic accidents determine a large number of injuries, sometimes fatal, every year. Among other factors affecting a driver's performance, an important role is played by stress which can decrease decision-making capabilities and situational awareness. In this perspective, it would be beneficial to develop a non-invasive driver stress monitoring system able to recognize the driver's altered state. In this study, a contactless procedure for drivers' stress state assessment by means of thermal infrared imaging was investigated. Thermal imaging was acquired during an experiment on a driving simulator, and thermal features of stress were investigated with comparison to a gold-standard metric (i.e., the stress index, SI) extracted from contact electrocardiography (ECG). A data-driven multivariate machine learning approach based on a non-linear support vector regression (SVR) was employed to estimate the SI through thermal features extracted from facial regions of interest (i.e., nose tip, nostrils, glabella). The predicted SI showed a good correlation with the real SI (r = 0.61, p = ~0). A two-level classification of the stress state (STRESS, SI ≥ 150, versus NO STRESS, SI < 150) was then performed based on the predicted SI. The ROC analysis showed a good classification performance with an AUC of 0.80, a sensitivity of 77%, and a specificity of 78%

TNF-α inhibits GDNF levels in Sertoli cells, through a NF-κB-dependent, HES1-dependent mechanism

Glial cell line-derived neurotrophic factor (GDNF) is a soluble molecule crucial for the regulation of the spermatogonial stem cells (SSC) of the testis. The effects of GDNF on target cells have been extensively described, but mechanisms underlying GDNF regulation are currently under investigation. In the nervous system, GDNF expression is regulated by pro-inflammatory cytokines including lipopolysaccharide (LPS), interleukin 1 beta (IL-1β), and tumor necrosis factor alpha (TNF-α) but the effect of these cytokines on GDNF expression in the testis is unclear

Deriving Natural Background Levels of Arsenic at the Meso-Scale Using Site-Specific Datasets: An Unorthodox Method

Arsenic is found in groundwater above regulatory limits in many countries and its origin is often from natural sources, making the definition of Natural Background Levels (NBLs) crucial. NBL is commonly assessed based on either dedicated small-scale monitoring campaigns or large-scale national/regional groundwater monitoring networks that may not grab local-scale heterogeneities. An alternative method is represented by site-specific monitoring networks in contaminated/polluted sites under remediation. As a main drawback, groundwater quality at these sites is affected by human activities. This paper explores the potential for groundwater data from an assemblage of site-specific datasets of contaminated/polluted sites to define NBLs of arsenic (As) at the meso-scale (order of 1000 km2). Common procedures for the assessment of human influence cannot be applied to this type of dataset due to limited data homogeneity. Thus, an \u201cunorthodox\u201d method is applied involving the definition of a consistent working dataset followed by a statistical identification and critical analysis of the outliers. The study was conducted in a highly anthropized area (Ferrara, N Italy), where As concentrations often exceed national threshold limits in a shallow aquifer. The results show that site-specific datasets, if properly pre-treated, are an effective alternative for the derivation of NBLs when regional monitoring networks fail to catch local-scale variability

Greenness and neuropsychiatric symptoms in dementia

Objectives: It is acknowledged that living in a green environment may help mental well-being and this may be especially true for vulnerable people. However, the relationship between greenness and neuropsychiatric symptoms in dementia has not been explored yet. Methods: We collected clinical, neuropsychiatric, and residential data from subjects with dementia living in the province of Modena, Northern Italy. Neuropsychiatric symptoms were measured with the Neuropsychiatry Inventory, a questionnaire administered to the caregiver who assesses the presence and severity of neuropsychiatric symptoms, including delusions, hallucinations, agitation/aggression, dysphoria/depression, anxiety, euphoria/elation, apathy/indifference, disinhibition, irritability/lability, aberrant motor behaviors, sleep disturbances, and appetite/eating changes. Normalized Difference Vegetation Index (NDVI) was used as a proxy of greenness. Regression models were constructed to study the association between greenness and neuropsychiatric features. Results: 155 patients with dementia were recruited. We found that greenness is variably associated with the risk of having neuropsychiatric symptoms. The risk of apathy was lower with lower levels of greenness (OR&nbsp;=&nbsp;0.42, 95% CI 0.19-0.91 for NDVI below the median value). The risk of psychosis was higher with lower levels of greenness but with more imprecise values (OR&nbsp;=&nbsp;1.77, 95% CI 0.84-3.73 for NDVI below the median value). Conclusion: Our results suggest a possible association between greenness and neuropsychiatric symptoms in people with dementia. If replicated in larger samples, these findings will pave the road for identifying innovative greening strategies and interventions that can improve mental health in dementia

Effect of some candidate genes on meat characteristics of three cattle breeds.

With the aim to assess if some molecular markers can help to select animals for meat characteristics, we studied 84 individuals equally representing the Marchigiana, Maremmana, and Holstein Friesian cattle breeds genotyped at 288 SNPs located within candidate genes. Several SNPs were found associated with meat quality parameters but with P which was higher than the Bonferroni threshold. However, several SNPs had a low P at different times during meat maturation, suggesting their involvement in the meat quality variation. Of particular interest for the biological role and potential for selection were: cathepsin G affecting MFI, IGF1R affecting pH and collagen XVIII affecting colour