A Novel Method for Online Detection of Faults Affecting Execution-Time in Multicore-Based Systems

This article proposes a bounded interference method, based on statistical evaluations, for online detection and tolerance of any fault capable of causing a deadline miss. The proposed method requires data that can be gathered during the profiling and worst-case execution time (WCET) analysis phase. This article describes the method, its application, and then it presents an avionic mixed-criticality use case for experimental evaluation, considering both dual-core and quad-core platforms. Results show that faults that can cause a timing violation are correctly identified while other faults that do not introduce a significant temporal interference can be tolerated to avoid high recovery overheads

Patient-Derived Xenografts of Non Small Cell Lung Cancer: Resurgence of an Old Model for Investigation of Modern Concepts of Tailored Therapy and Cancer Stem Cells

Current chemotherapy regimens have unsatisfactory results in most advanced solid tumors. It is therefore imperative to devise novel therapeutic strategies and to optimize selection of patients, identifying early those who could benefit from available treatments. Mouse models are the most valuable tool for preclinical evaluation of novel therapeutic strategies in cancer and, among them, patient-derived xenografts models (PDX) have made a recent comeback in popularity. These models, obtained by direct implants of tissue fragments in immunocompromised mice, have great potential in drug development studies because they faithfully reproduce the patient's original tumor for both immunohistochemical markers and genetic alterations as well as in terms of response to common therapeutics They also maintain the original tumor heterogeneity, allowing studies of specific cellular subpopulations, including their modulation after drug treatment. Moreover PDXs maintain at least some aspects of the human microenvironment for weeks with the complete substitution with murine stroma occurring only after 2-3 passages in mouse and represent therefore a promising model for studies of tumor-microenvironment interaction. This review summarizes our present knowledge on mouse preclinical cancer models, with a particular attention on patient-derived xenografts of non small cell lung cancer and their relevance for preclinical and biological studies

LKB1 Down-Modulation by miR-17 Identifies Patients With NSCLC Having Worse Prognosis Eligible for Energy-Stress–Based Treatments

Abstract Introduction Preclinical models recently unveiled the vulnerability of LKB1/KRAS comutated NSCLC to metabolic stress-based treatments. Because miR-17 is a potential epigenetic regulator of LKB1, we hypothesized that wild-type LKB1 (LKB1WT) NSCLC with high miR-17 expression may be sensitive to an energetic stress condition, and eligible for metabolic frailties-based therapeutic intervention. Methods We took advantage of NSCLC cell lines with different combinations of KRAS mutation and LKB1 deletion and of patient-derived xenografts (PDXs) with high (LKB1WT/miR-17 high) or low (LKB1WT/miR-17 low) miR-17 expression. We evaluated LKB1 pathway impairment and apoptotic response to metformin. We retrospectively evaluated LKB1 and miR-17 expression levels in tissue specimens of patients with NSCLC and PDXs. In addition, a lung cancer series from The Cancer Genome Atlas data set was analyzed for miR-17 expression and potential correlation with clinical features. Results We identified miR-17 as an epigenetic regulator of LKB1 in NSCLC and confirmed targeting of miR-17 to LKB1 3′ untranslated region by luciferase reporter assay. We found that miR-17 overexpression functionally impairs the LKB1/AMPK pathway. Metformin treatment prompted apoptosis on miR-17 overexpression only in LKB1WT cell lines, and in LKB1WT/miR-17 high PDXs. A retrospective analysis in patients with NSCLC revealed an inverse correlation between miR-17 and LKB1 expression and highlighted a prognostic role of miR-17 expression in LKB1WT patients, which was further confirmed by The Cancer Genome Atlas data analysis. Conclusions We identified miR-17 as a mediator of LKB1 expression in NSCLC tumors. This study proposes a miR-17 expression score potentially exploitable to discriminate LKB1WT patients with NSCLC with impaired LKB1 expression and poor outcome, eligible for energy-stress-based treatments

Myocardial involvement during the early course of type 2 diabetes mellitus: usefulness of Myocardial Performance Index

To evaluate whether myocardial performance index detects a subclinical impairment of left ventricular systolic and diastolic function in patients with early stage of type 2 diabetes, without coronary artery disease, with or without hypertension. Furthermore, to evaluate whether some echocardiographic parameters relate to the metabolic control. Fourty-five consecutive male patients (mean age 52.5 years) with type 2 diabetes mellitus of recent onset (23 hypertensives and 22 normotensives) and 22 age matched healthy controls males were analysed. All participants had normal exercise ECG. All subjects underwent standard and Doppler echocardiography for the assessment of the isovolumic Doppler time interval and Doppler-derived myocardial performance index. In all diabetic patients a glycated haemoglobin test was also performed

Beyond Traditional Morphological Characterization of Lung Neuroendocrine Neoplasms: In Silico Study of Next-Generation Sequencing Mutations Analysis across the Four World Health Organization Defined Groups

Lung neuroendocrine neoplasms (LNENs) classes, as proposed by the World Health Organization 2015, do not provide properly prognostic and therapeutic indications. In fact, high-throughput molecular analysis, based on next-generation sequencing, identified novel molecular subgroups, associated with different genomic signatures, that could pave the way for alternative therapeutic approaches. The present review, coupled with in silico molecular analysis, could show the current genomic alterations state in actual LNENS groups. Interestingly our manuscript suggests that the molecular novelties could improve the LNENs therapeutics efficacy. In more detail, we reported the differences of gene alterations and mutational rate between LNENS, confirming the central pathogenetic role given by a different mutational rate in chromatin remodeling genes and tumor suppressors TP53-RB1. In conclusion, our results underlined that a further molecular layer is needed to improve the efficacy of LNENs medical treatment.Lung neuroendocrine neoplasms (LNENs) represent a rare and heterogeneous population of lung tumors. LNENs incidence rate has increased dramatically over the past 30 years. The current World Health Organization LNENs classification (WHO 2015), distinguished four LNENs prognostic categories, according to their morphology, necrosis amount and mitotic count: typical carcinoid (TC), atypical-carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC) and small cell lung cancer (SCLC). At present, due to their rarity and biological heterogeneity there is still no consensus on the best therapeutic approach. Next-generation-sequencing analysis showed that WHO 2015 LNENs classes, could be characterized also by specific molecular alterations: frequently mutated genes involving chromatin remodeling and generally characterized by low mutational burden (MB) are frequently detected in both TC and AC; otherwise, TP53 and RB1 tumor suppressor genes alterations and high MB are usually detected in LCNEC and SCLC. We provide an overview concerning gene mutations in each WHO 2015 LNENs class in order to report the current LNENs mutational status as potential tool to better understand their clinical outcome and to drive medical treatment

Metformin Enhances Cisplatin-Induced Apoptosis and Prevents Resistance to Cisplatin in Co-mutated KRAS/LKB1 NSCLC

Abstract Introduction We hypothesized that activating KRAS mutations and inactivation of the liver kinase B1 (LKB1) oncosuppressor can cooperate to sustain NSCLC aggressiveness. We also hypothesized that the growth advantage of KRAS/LKB1 co-mutated tumors could be balanced by higher sensitivity to metabolic stress conditions, such as metformin treatment, thus revealing new strategies to target this aggressive NSCLC subtype. Methods We retrospectively determined the frequency and prognostic value of KRAS/LKB1 co-mutations in tissue specimens from NSCLC patients enrolled in the TAILOR trial. We generated stable LKB1 knockdown and LKB1-overexpressing isogenic H1299 and A549 cell variants, respectively, to test the in vitro efficacy of metformin. We also investigated the effect of metformin on cisplatin-resistant CD133+ cells in NSCLC patient-derived xenografts. Results We found a trend towards worse overall survival in patients with KRAS/LKB1 co-mutated tumors as compared to KRAS-mutated ones (hazard ratio: 2.02, 95% confidence interval: 0.94–4.35, p = 0.072). In preclinical experiments, metformin produced pro-apoptotic effects and enhanced cisplatin anticancer activity specifically in KRAS/LKB1 co-mutated patient-derived xenografts. Moreover, metformin prevented the development of acquired tumor resistance to 5 consecutive cycles of cisplatin treatment (75% response rate with metformin-cisplatin as compared to 0% response rate with cisplatin), while reducing CD133+ cells. Conclusions LKB1 mutations, especially when combined with KRAS mutations, may define a specific and more aggressive NSCLC subtype. Metformin synergizes with cisplatin against KRAS/LKB1 co-mutated tumors, and may prevent or delay the onset of resistance to cisplatin by targeting CD133+ cancer stem cells. This study lays the foundations for combining metformin with standard platinum-based chemotherapy in the treatment of KRAS/LKB1 co-mutated NSCLC

Metformin +/- cyclic fasting mimicking diet in combination with platinum-pemetrexed chemotherapy for advanced LKB1 inactive lung adenocarcinoma: The FAME trial

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Improved Prognostic Prediction in Never-Smoker Lung Cancer Patients by Integration of a Systemic Inflammation Marker with Tumor Immune Contexture Analysis

Almost 25% of lung cancers (LCs) occur in never-smokers. LC inflammatory profile, based on plasma C-reactive protein levels (CRP), predicts mortality, independently by smoking-status. We hypothesized that: CRP could be associated with tumor immune contexture (TIC) in never-smokers and both these two parameters may improve their prognosis. Sixty-eight never-smokers LC patients with high or low CRP were selected. The programmed cell death protein 1 (PD-1) and its ligand (PD-L1), the human leukocyte antigens (HLA-DR and HLA-I), CD8, CD4, CD3, CD33, CD163, and CD68 were evaluated by immunohistochemistry on surgical samples given TIC evaluation. The classification model based on TIC scores was generated by Classification and Regression Tree analysis. Tumor mutational burden was evaluated by targeted next-generation sequencing. Exclusively high CRP (H-CRP) subset showed PD-L1 expression in 35% of LC as well as lower HLA-I and HLA-DR in their stromal cells. CD3, CD4, CD8, HLA-I, HLA-DR tumor cells staining were associated with a "low inflammatory profile" subset. CRP and LC immune profiles drive clinical outcome: 5-year survival 88% against 8% was associated with low and high-risk profiles (p< 0.0001). Clinical outcome prediction in never-smoker LC patients may be improved by both CRP and tumor immune contexture evaluation

Systematic versus on-demand early palliative care: results from a multicentre, randomised clinical trial

Background Early palliative care (EPC) in oncology has been shown to have a positive impact on clinical outcome, quality-of-care outcomes, and costs. However, the optimal way for activating EPC has yet to be defined. Methods This prospective, multicentre, randomised study was conducted on 207 outpatients with metastatic or locally advanced inoperable pancreatic cancer. Patients were randomised to receive ‘standard cancer care plus on-demand EPC’ (n = 100) or ‘standard cancer care plus systematic EPC’ (n = 107). Primary outcome was change in quality of life (QoL) evaluated through the Functional Assessment of Cancer Therapy – Hepatobiliary questionnaire between baseline (T0) and after 12 weeks (T1), in particular the integration of physical, functional, and Hepatic Cancer Subscale (HCS) combined in the Trial Outcome Index (TOI). Patient mood, survival, relatives' satisfaction with care, and indicators of aggressiveness of care were also evaluated. Findings The mean changes in TOI score and HCS score between T0 and T1 were −4.47 and −0.63, with a difference between groups of 3.83 (95% confidence interval [CI] 0.10–7.57) (p = 0.041), and −2.23 and 0.28 (difference between groups of 2.51, 95% CI 0.40–4.61, p = 0.013), in favour of interventional group. QoL scores at T1 of TOI scale and HCS were 84.4 versus 78.1 (p = 0.022) and 52.0 versus 48.2 (p = 0.008), respectively, for interventional and standard arm. Until February 2016, 143 (76.9%) of the 186 evaluable patients had died. There was no difference in overall survival between treatment arms. Interpretations Systematic EPC in advanced pancreatic cancer patients significantly improved QoL with respect to on-demand EPC

Impact of different exposure models and spatial resolution on the long-term effects of air pollution.

Abstract Long-term exposure to air pollution has been related to mortality in several epidemiological studies. The investigations have assessed exposure using various methods achieving different accuracy in predicting air pollutants concentrations. The comparison of the health effects estimates are therefore challenging. This paper aims to compare the effect estimates of the long-term effects of air pollutants (particulate matter with aerodynamic diameter less than 10 μm, PM10, and nitrogen dioxide, NO2) on cause-specific mortality in the Rome Longitudinal Study, using exposure estimates obtained with different models and spatial resolutions. Annual averages of NO2 and PM10 were estimated for the year 2015 in a large portion of the Rome urban area (12 × 12 km2) applying three modelling techniques available at increasing spatial resolution: 1) a chemical transport model (CTM) at 1km resolution; 2) a land-use random forest (LURF) approach at 200m resolution; 3) a micro-scale Lagrangian particle dispersion model (PMSS) taking into account the effect of buildings structure at 4 m resolution with results post processed at different buffer sizes (12, 24, 52, 100 and 200 m). All the exposures were assigned at the residential addresses of 482,259 citizens of Rome 30+ years of age who were enrolled on 2001 and followed-up till 2015. The association between annual exposures and natural-cause, cardiovascular (CVD) and respiratory (RESP) mortality were estimated using Cox proportional hazards models adjusted for individual and area-level confounders. We found different distributions of both NO2 and PM10 concentrations, across models and spatial resolutions. Natural cause and CVD mortality outcomes were all positively associated with NO2 and PM10 regardless of the model and spatial resolution when using a relative scale of the exposure such as the interquartile range (IQR): adjusted Hazard Ratios (HR), and 95% confidence intervals (CI), of natural cause mortality, per IQR increments in the two pollutants, ranged between 1.012 (1.004, 1.021) and 1.018 (1.007, 1.028) for the different NO2 estimates, and between 1.010 (1.000, 1.020) and 1.020 (1.008, 1.031) for PM10, with a tendency of larger effect for lower resolution exposures. The latter was even stronger when a fixed value of 10 μg/m3 is used to calculate HRs. Long-term effects of air pollution on mortality in Rome were consistent across different models for exposure assessment, and different spatial resolutions