Early Detection and Investigation of Extracellular Vesicles Biomarkers in Breast Cancer

Breast cancer (BC) is the most commonly diagnosed malignant tumor in women worldwide, and the leading cause of cancer death in the female population. The percentage of patients experiencing poor prognosis along with the risk of developing metastasis remains high, also affecting the resistance to current main therapies. Cancer progression and metastatic development are no longer due entirely to their intrinsic characteristics, but also regulated by signals derived from cells of the tumor microenvironment. Extracellular vesicles (EVs) packed with DNA, RNA, and proteins, are the most attractive targets for both diagnostic and therapeutic applications, and represent a decisive challenge as liquid biopsy-based markers. Here we performed a study based on a multiplexed phenotyping flow cytometric approach to characterize BC-derived EVs from BC patients and cell lines, through the detection of multiple antigens. Our data reveal the expression of EVs-related biomarkers derived from BC patient plasma and cell line supernatants, suggesting that EVs could be exploited for characterizing and monitoring disease progression

Investigating the Use of Geometric Semantic Operators in Vectorial Genetic Programming

Azzali, I., Vanneschi, L., & Giacobini, M. (2020). Investigating the Use of Geometric Semantic Operators in Vectorial Genetic Programming. In T. Hu, N. Lourenço, E. Medvet, & F. Divina (Eds.), Genetic Programming - 23rd European Conference, EuroGP 2020, Held as Part of EvoStar 2020, Proceedings (pp. 52-67). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12101 LNCS). Springer. https://doi.org/10.1007/978-3-030-44094-7_4 ------- This work was partially supported by FCT, Portugal through funding of LASIGE Research Unit (UID/CEC/00408/2019), and projects PREDICT (PTDC/CCI-IF/29877/2017), BINDER (PTDC/CCI-INF/29168/2017), GADgET (DSAIPA/DS/0022/2018) and AICE (DSAIPA/DS/0113/2019).Vectorial Genetic Programming (VE_GP) is a new GP approach for panel data forecasting. Besides permitting the use of vectors as terminal symbols to represent time series and including aggregation functions to extract time series features, it introduces the possibility of evolving the window of aggregation. The local aggregation of data allows the identification of meaningful patterns overcoming the drawback of considering always the previous history of a series of data. In this work, we investigate the use of geometric semantic operators (GSOs) in VE_GP, comparing its performance with traditional GP with GSOs. Experiments are conducted on two real panel data forecasting problems, one allowing the aggregation on moving windows, one not. Results show that classical VE_GP is the best approach in both cases in terms of predictive accuracy, suggesting that GSOs are not able to evolve efficiently individuals when time series are involved. We discuss the possible reasons of this behaviour, to understand how we could design valuable GSOs for time series in the future.authorsversionpublishe

A multi-element psychosocial intervention for early psychosis (GET UP PIANO TRIAL) conducted in a catchment area of 10 million inhabitants: study protocol for a pragmatic cluster randomized controlled trial

Multi-element interventions for first-episode psychosis (FEP) are promising, but have mostly been conducted in non-epidemiologically representative samples, thereby raising the risk of underestimating the complexities involved in treating FEP in 'real-world' services

Well-posedness, positivity, and time asymptotics properties for a reaction-diffusion model of plankton communities, involving a rational nonlinearity with singularity

In this work, we consider a reaction-diffusion system, modeling the interaction between nutrients, phytoplankton, and zooplankton. Using a semigroup approach inL2, we prove global existence, uniqueness, and positivity of the solutions. The nonlinearity is handled by providing estimates inL infinity, allowing to deal with most of the functional responses that describe predator/prey interactions (Holling I, II, III, Ivlev) in ecology. The paper finally exhibits some time asymptotic properties of the solutions

The Italian version of the 16-item prodromal questionnaire (iPQ-16): field-test and psychometric features

OBJECTIVE: Among current early screeners for psychosis-risk states, the Prodromal Questionnaire-16 items (PQ-16) is often used. We aimed to assess validity and reliability of the Italian version of the PQ-16 in a young adult help-seeking population. METHODS: We included 154 individuals aged 18-35years seeking help at the Reggio Emilia outpatient mental health services in a large semirural catchment area (550.000 inhabitants). Participants completed the Italian version of the PQ-16 (iPQ-16) and were subsequently evaluated with the Comprehensive Assessment of At-Risk Mental States (CAARMS). We examined diagnostic accuracy (i.e. specificity, sensitivity, negative and positive likelihood ratios, and negative and positive predictive values) and content, convergent, and concurrent validity between PQ-16 and CAARMS using Cronbach's alpha, Spearman's rho, and Cohen's kappa, respectively. We also tested the validity of the adopted PQ-16 cut-offs through Receiver Operating Characteristic (ROC) curves plotted against CAARMS diagnoses and the 1-year predictive validity of the PQ-16. RESULTS: The iPQ-16 showed high internal consistency and acceptable diagnostic accuracy and concurrent validity. ROC analyses pointed to a cut-off score of ≥5 as best cut-off. After 12months of follow-up, 8.7% of participants with a PQ-16 symptom total score of ≥5 who were below the CAARMS psychosis threshold at the baseline, developed a psychotic disorder. CONCLUSIONS: Psychometric properties of the iPQ-16 were satisfactory

Adolescents at ultra-high risk of psychosis in Italian neuropsychiatry services: prevalence, psychopathology and transition rate

Studies in adolescents on ultra-high risk (UHR) and basic symptoms (BS) criteria for psychosis prediction are scarce. In Italy, early interventions in psychosis are less widespread than in other European countries. In the present study, we (1) assessed the clinical relevance of a UHR diagnosis [according to the comprehensive assessment of at-risk mental states (CAARMS) criteria] to promote the implementation of specific services for UHR adolescents into the Italian health care system; (2) described severity of positive, negative, general, and basic symptoms in UHR adolescents compared to adolescents with first-episode psychosis (FEP) and non-UHR adolescents (i.e., individuals who did not meet CAARMS criteria for UHR or FEP); and (3) investigated the predictive validity of UHR criteria in relation to BS criteria. Seventy-nine adolescents (aged 13-18 years) were assessed with the CAARMS, the positive and negative syndrome scale (PANSS), and the schizophrenia proneness instrument, child and youth version (SPI-CY). Both UHR (n = 25) and FEP (n = 11) had significantly higher PANSS subscale scores compared to non-UHR (n = 43). UHR had significantly lower PANSS-positive symptom scores than FEP, but similar global functioning and PANSS-negative symptoms and general psychopathology scores. Compared to non-UHR, both FEP and UHR had more severe thought and perception BS disturbances, and significantly more often met BS criteria. After 12 months, 2 of 20 (10%) UHR had transitioned to psychosis. They also met both BS criteria. Given the uncertain outcome of UHR adolescents, future research is needed to determine whether the combined assessment of BS with UHR symptoms can improve the accuracy of psychosis prediction in adolescence