Dynamic Perimeter Surveillance of Multiagent Systems: A Swarm-Based Approach.

In this article, a novel approach to generating kinematic state trajectories for single-integrator multiagent systems is developed with the aim of addressing cooperative surveillance tasks of rectangular areas. In particular, the key idea consists in driving the involved agents within a so-called containment region while simultaneously reaming outside a forbidden area around the prescribed target. As one of its main features, the proposed kinematics allows the whole multiagent configuration to rotate safely along the perimeter under both full and partial connectivity properties of the underlying topology graph. Steady-state conditions are analyzed and sufficient conditions are derived in terms of kinematic model parameters. Finally, a set of simulations is aimed at showing the capability of the kinematic descriptions to quickly buttonhole the containment region and to keep a rotating behavior around the target.

Automatic Stones Classification through a CNN-Based Approach.

This paper presents an automatic recognition system for classifying stones belonging to different Calabrian quarries (Southern Italy). The tool for stone recognition has been developed in the SILPI project (acronym of "Sistema per l'Identificazione di Lapidei Per Immagini"), financed by POR Calabria FESR-FSE 2014-2020. Our study is based on the Convolutional Neural Network (CNNs) that is used in literature for many different tasks such as speech recognition, neural language processing, bioinformatics, image classification and much more. In particular, we propose a two-stage hybrid approach based on the use of a model of Deep Learning (DL), in our case the CNN, in the first stage and a model of Machine Learning (ML) in the second one. In this work, we discuss a possible solution to stones classification which uses a CNN for the feature extraction phase and the Softmax or Multinomial Logistic Regression (MLR), Support Vector Machine (SVM), k-Nearest Neighbors (kNN), Random Forest (RF) and Gaussian Naive Bayes (GNB) ML techniques in order to perform the classification phase basing our study on the approach called Transfer Learning (TL). We show the image acquisition process in order to collect adequate information for creating an opportune database of the stone typologies present in the Calabrian quarries, also performing the identification of quarries in the considered region. Finally, we show a comparison of different DL and ML combinations in our Two-Stage Hybrid Model solution.

A Swarm-Based Distributed Model Predictive Control Scheme for Autonomous Vehicle Formations in Uncertain Environments.

In this article, a novel distributed model predictive control architecture is proposed for the coordination and control of multivehicle formations moving within uncertain environments. As one of its main merits, multiagent swarm modeling and leader-follower configurations are jointly exploited within an ad hoc model predictive control framework to reduce as much as possible the use of onboard sensors that is essential in long-range missions. Moreover, the feasibility and asymptotic closed-loop stability of the resulting scheme are formally proved. Finally, a laboratory experiment is used to show the effectiveness of the proposed algorithm with particular attention to the follower capability of operating in a so-called blind fashion.

Running power: lab based vs. portable devices measurements and its relationship with aerobic power.

In recent years, different companies have developed devices that estimate "running power". The main objective of this paper is to evaluate the effect of running speed on aerobic and running powers measured using force plates and by different devices. The second objective is to evaluate the relationship between aerobic power and running powers measured using force plates and by different devices. We enrolled 11 subjects in the study, they performed 5-min running trials at 2.22, 2.78, 3.33, 3.89 and 4.44 m/s respectively on a force-measuring treadmill while we collected metabolic data. We calculated running power as the dot product of ground reaction force and velocity of the centre of mass and compared it to the running power estimates of three devices: Skillrun (Technogym), Stryd Summit Powermeter (Stryd) and Garmin HRM-Run (Garmin). We found statistically significant linear correlations with running powers measured by all devices and running speed. Although absolute running power measurements were different among devices, an increase of 1 m/s in running speed translated to an increase of 0.944 W/kg in running power (p < 0.001). We found statistically significant linear correlations with running powers measured by all devices and aerobic power, in particular: as aerobic power increases by 1 W/kg, running power increases by 0.218 W/kg for all devices (p < 0.001). For level treadmill running, across speeds, running power measured by commercially available devices reflects force-based measurements and it can be a valuable metric, providing quasi real-time feedback during training sessions and competitions.HighlightsWe evaluated the effect of running speed on aerobic and running powers measured using force plates and by different devices.We also compared the relationship between aerobic power and running powers measured using force plates and by different devices.We found statistically significant linear correlations with running powers measured by all devices and aerobic power, in particular: as aerobic power increases by 1 W/kg, running power increases by 0.218 W/kg for all devices.For level treadmill running, across speeds, running power measured by commercially available devices reflects force-based measurements and it can be a valuable metric, providing quasi real-time feedback during training sessions and competitions.

Clustering Methods for Microarray Data Sets.

Microarrays are experimental methods that can provide information about gene expression and SNP data that hold great potential for new understanding, driving advances in functional genomics and clinical and molecular biology. Cluster analysis is used to analyze data that are not a priori to contain any specific subgroup. The goal is to use the data itself to recognize meaningful and informative subgroups. Also, cluster analysis helps data reduction purposes, exposes hidden patterns, and generates hypotheses regarding the relationship between genes and phenotypes. This chapter outlines a collection of cluster methods suitable for the analysis of microarray data sets.

Parameter Estimation and an Extended Predictive-Based Tuning Method for a Lab-Scale Distillation Column.

The present study proposes a new PI controller tuning method using extended predictive control (EPC). The PI controller parameter values are calculated using the EPC controller output and its closed-loop response. This provides a simple and an effective tuning strategy which results in an improved closed-loop response compared to conventional tuning methods. The tuning methodology is applicable for single input single output and multi input multi output stable processes. Simulation and experimental results reveal the efficacy of the method under plant uncertainty conditions.

A Kinematic Model for Swarm Finite-Time Trajectory Tracking.

This paper focuses on the trajectory tracking problem for a swarm of mobile agents. A kinematic model describing the interactions and evolutions of the swarm members is proposed and its main properties are analyzed emphasizing that the agents centroid is ensured to track in finite-time a given reference trajectory and that the agents reach an aggregation in finite-time in a hyper-ball moving around the centroid path. One of the main characteristics of the model is the presence of an interaction matrix, between agents coordinates, which allows to define some properties of the swarm allowing the creation of different forms of agents aggregations, i.e., spheres, ellipsoids, straight lines, etc. Indeed swarm properties related to the agents configuration around the performed path along with agents interactions and absence of collisions are analyzed depending on the chosen interaction matrix.

Developmental changes in plasticity, synaptic, glia, and connectivity protein levels in rat medial prefrontal cortex.

The medial prefrontal cortex (mPFC) plays a critical role in complex brain functions including decision-making, integration of emotional, and cognitive aspects in memory processing and memory consolidation. Because relatively little is known about the molecular mechanisms underlying its development, we quantified rat mPFC basal expression levels of sets of plasticity, synaptic, glia, and connectivity proteins at different developmental ages. Specifically, we compared the mPFC of rats at postnatal day 17 (PN17), when they are still unable to express long-term contextual and spatial memories, to rat mPFC at PN24, when they have acquired the ability of long-term memory expression and finally to the mPFC of adult rats. We found that, with increased age, there are remarkable and significant decreases in markers of cell activation and significant increases in proteins that mark synaptogenesis and synapse maturation. Furthermore, we found significant changes in structural markers over the ages, suggesting that structural connectivity of the mPFC increases over time. Finally, the substantial biological difference in mPFC at different ages suggest caution in extrapolating conclusions from brain plasticity studies conducted at different developmental stages.

Measuring PI3K Activation: Clinicopathologic, Immunohistochemical, and RNA Expression Analysis in Prostate Cancer.

UNLABELLED: Assessing the extent of PI3K pathway activity in cancer is vital to predicting sensitivity to PI3K-targeting drugs, but the best biomarker of PI3K pathway activity in archival tumor specimens is unclear. Here, PI3K pathway activation was assessed, in clinical tissue from 1,021 men with prostate cancers, using multiple pathway nodes that include PTEN, phosphorylated AKT (pAKT), phosphorylated ribosomal protein S6 (pS6), and stathmin. Based on these markers, a 9-point score of PI3K activation was created using the combined intensity of the 4-markers and analyzed its association with proliferation (Ki67), apoptosis (TUNEL), and androgen receptor (AR) status, as well as pathologic features and cancer-specific outcomes. In addition, the PI3K activation score was compared with mRNA expression profiling data for a large subset of men. Interestingly, those tumors with higher PI3K activation scores also had higher Gleason grade (P = 0.006), increased AR (r = 0.37; P < 0.001) and Ki67 (r = 0.24; P < 0.001), and decreased TUNEL (r = -0.12; P = 0.003). Although the PI3K activation score was not associated with an increased risk of lethal outcome, a significant interaction between lethal outcome, Gleason and high PI3K score (P = 0.03) was observed. Finally, enrichment of PI3K-specific pathways was found in the mRNA expression patterns differentiating the low and high PI3K activation scores; thus, the 4-marker IHC score of PI3K pathway activity correlates with features of PI3K activation. IMPLICATIONS: The relationship of this activation score to sensitivity to anti-PI3K agents remains to be tested but may provide more precision guidance when selecting patients for these therapies.

Patterns of psychiatric medication use among nationally representative long-term cancer survivors and controls.

BACKGROUND: Investigations of long-term cancer survivors (LTCS) indicate that this population is not appreciably different from cancer-naive peers with respect to several neuropsychiatric domains. The current study sought to determine whether differences in psychiatric medication use might help to explain the negative findings. METHODS: In a nationally representative sample, 5692 subjects were queried for cancer history, psychiatric diagnoses, and psychotropic medication use. The LTCS were defined as those individuals who were ≥5 years from diagnosis and whose cancer was in remission or cured. Odds ratios and 95% confidence intervals were obtained from multivariable logistic regression models evaluating the relationship between cancer status and use of psychiatric medications. The interaction between case/control status and psychiatric diagnoses was also tested in a logistic regression model to predict psychotropic medication use. RESULTS: A total of 225 participants met the criteria for LTCS and 3953 met the criteria for cancer-naive controls (CNC). The LTCS were no more likely than CNC to carry a psychiatric diagnosis. Despite the LTCS reporting somewhat greater psychotropic medication use compared with the CNC (28.8% vs 22.3%), unadjusted and adjusted differences did not reach statistical significance, possibly due to sample size. The interaction between case/control status and carrying a psychiatric diagnosis was not found to be significantly associated with receiving a psychiatric medication. CONCLUSIONS: LTCS and CNC demonstrated comparable rates of psychiatric prescription medication use. The relationship between taking a psychiatric medication and carrying a psychiatric diagnosis was not found to be significantly different between the case and control groups. These findings contribute to an emerging hypothesis that in general LTCS are not a particularly psychiatrically vulnerable group.

A novel direct activator of AMPK inhibits prostate cancer growth by blocking lipogenesis.

5'AMP-activated kinase (AMPK) constitutes a hub for cellular metabolic and growth control, thus representing an ideal therapeutic target for prostate cancers (PCas) characterized by increased lipogenesis and activation of mTORC1 pathway. However, whether AMPK activation itself is sufficient to block cancer cell growth remains to be determined. A small molecule screening was performed and identified MT 63-78, a specific and potent direct AMPK activator. Here, we show that direct activation of AMPK inhibits PCa cell growth in androgen sensitive and castration resistant PCa (CRPC) models, induces mitotic arrest, and apoptosis. In vivo, AMPK activation is sufficient to reduce PCa growth, whereas the allelic loss of its catalytic subunits fosters PCa development. Importantly, despite mTORC1 blockade, the suppression of de novo lipogenesis is the underpinning mechanism responsible for AMPK-mediated PCa growth inhibition, suggesting AMPK as a therapeutic target especially for lipogenesis-driven PCas. Finally, we demonstrate that MT 63-78 enhances the growth inhibitory effect of AR signaling inhibitors MDV3100 and abiraterone. This study thus provides a rationale for their combined use in CRPC treatment.

Differential expression of S6K2 dictates tissue-specific requirement for S6K1 in mediating aberrant mTORC1 signaling and tumorigenesis.

The S6K1 and S6K2 kinases are considered important mTOR signaling effectors, yet their contribution to tumorigenesis remains unclear. Aberrant mTOR activation is a frequent event in cancer that commonly results from heterozygous loss of PTEN. Here, we show for the first time a differential protein expression between S6K1 and S6K2 in both mouse and human tissues. Additionally, the inactivation of S6k1 in the context of Pten heterozygosity (Pten(+/-)) suggests a differential requirement for this protein across multiple tissues. This tissue specificity appears to be governed by the relative protein expression of S6k2. Accordingly, we find that deletion of S6k1 markedly impairs Pten(+/-) mediated adrenal tumorigenesis, specifically due to low expression of S6k2. Concomitant observation of low S6K2 levels in the human adrenal gland supports the development of S6K1 inhibitors for treatment of PTEN loss-driven pheochromocytoma.

Fatty acid synthase polymorphisms, tumor expression, body mass index, prostate cancer risk, and survival.

PURPOSE: Fatty acid synthase (FASN) regulates de novo lipogenesis, body weight, and tumor growth. We examined whether common germline single nucleotide polymorphisms (SNPs) in the FASN gene affect prostate cancer (PCa) risk or PCa-specific mortality and whether these effects vary by body mass index (BMI). METHODS: In a prospective nested case-control study of 1,331 white patients with PCa and 1,267 age-matched controls, we examined associations of five common SNPs within FASN (and 5 kb upstream/downstream, R(2) > 0.8) with PCa incidence and, among patients, PCa-specific death and tested for an interaction with BMI. Survival analyses were repeated for tumor FASN expression (n = 909). RESULTS: Four of the five SNPs were associated with lethal PCa. SNP rs1127678 was significantly related to higher BMI and interacted with BMI for both PCa risk (P(interaction) = .004) and PCa mortality (P(interaction) = .056). Among overweight men (BMI > or = 25 kg/m(2)), but not leaner men, the homozygous variant allele carried a relative risk of advanced PCa of 2.49 (95% CI, 1.00 to 6.23) compared with lean men with the wild type. Overweight patients carrying the variant allele had a 2.04 (95% CI, 1.31 to 3.17) times higher risk of PCa mortality. Similarly, overweight patients with elevated tumor FASN expression had a 2.73 (95% CI, 1.05 to 7.08) times higher risk of lethal PCa (P(interaction) = .02). CONCLUSION: FASN germline polymorphisms were significantly associated with risk of lethal PCa. Significant interactions of BMI with FASN polymorphisms and FASN tumor expression suggest FASN as a potential link between obesity and poor PCa outcome and raise the possibility that FASN inhibition could reduce PCa-specific mortality, particularly in overweight men.

Identification of the miR-106b~25 microRNA cluster as a proto-oncogenic PTEN-targeting intron that cooperates with its host gene MCM7 in transformation.

PTEN (phosphatase and tensin homolog deleted on chromosome 10) is a tumor suppressor that antagonizes signaling through the phosphatidylinositol 3-kinase-Akt pathway. We have demonstrated that subtle decreases in PTEN abundance can have critical consequences for tumorigenesis. Here, we used a computational approach to identify miR-22, miR-25, and miR-302 as three PTEN-targeting microRNA (miRNA) families found within nine genomic loci. We showed that miR-22 and the miR-106b~25 cluster are aberrantly overexpressed in human prostate cancer, correlate with abundance of the miRNA processing enzyme DICER, and potentiate cellular transformation both in vitro and in vivo. We demonstrated that the intronic miR-106b~25 cluster cooperates with its host gene MCM7 in cellular transformation both in vitro and in vivo, so that the concomitant overexpression of MCM7 and the miRNA cluster triggers prostatic intraepithelial neoplasia in transgenic mice. Therefore, the MCM7 gene locus delivers two simultaneous oncogenic insults when amplified or overexpressed in human cancer. Thus, we have uncovered a proto-oncogenic miRNA-dependent network for PTEN regulation and defined the MCM7 locus as a critical factor in initiating prostate tumorigenesis.

Preclinical model of organotypic culture for pharmacodynamic profiling of human tumors.

Predicting drug response in cancer patients remains a major challenge in the clinic. We have perfected an ex vivo, reproducible, rapid and personalized culture method to investigate antitumoral pharmacological properties that preserves the original cancer microenvironment. Response to signal transduction inhibitors in cancer is determined not only by properties of the drug target but also by mutations in other signaling molecules and the tumor microenvironment. As a proof of concept, we, therefore, focused on the PI3K/Akt signaling pathway, because it plays a prominent role in cancer and its activity is affected by epithelial-stromal interactions. Our results show that this culture model preserves tissue 3D architecture, cell viability, pathway activity, and global gene-expression profiles up to 5 days ex vivo. In addition, we show pathway modulation in tumor cells resulting from pharmacologic intervention in ex vivo culture. This technology may have a significant impact on patient selection for clinical trials and in predicting response to small-molecule inhibitor therapy.

An oncogene-tumor suppressor cascade drives metastatic prostate cancer by coordinately activating Ras and nuclear factor-kappaB.

Metastasis is responsible for the majority of prostate cancer-related deaths; however, little is known about the molecular mechanisms that underlie this process. Here we identify an oncogene-tumor suppressor cascade that promotes prostate cancer growth and metastasis by coordinately activating the small GTPase Ras and nuclear factor-kappaB (NF-kappaB). Specifically, we show that loss of the Ras GTPase-activating protein (RasGAP) gene DAB2IP induces metastatic prostate cancer in an orthotopic mouse tumor model. Notably, DAB2IP functions as a signaling scaffold that coordinately regulates Ras and NF-kappaB through distinct domains to promote tumor growth and metastasis, respectively. DAB2IP is suppressed in human prostate cancer, where its expression inversely correlates with tumor grade and predicts prognosis. Moreover, we report that epigenetic silencing of DAB2IP is a key mechanism by which the polycomb-group protein histone-lysine N-methyltransferase EZH2 activates Ras and NF-kappaB and triggers metastasis. These studies define the mechanism by which two major pathways can be simultaneously activated in metastatic prostate cancer and establish EZH2 as a driver of metastasis.

The chemokine receptor CX3CR1 is involved in the neural tropism and malignant behavior of pancreatic ductal adenocarcinoma.

Tumor perineural dissemination is a hallmark of human pancreatic ductal adenocarcinoma (PDAC) and represents a major source of local tumor recurrence after surgery. In this study, we provide in vitro and in vivo evidence that the chemokine receptor CX3CR1 may be involved in the neurotropism of PDAC cells to local peripheral nerves. Neoplastic cells from PDAC cell lines and surgical specimens express the chemokine receptor CX3CR1, absent in normal pancreatic ducts. Its unique ligand, the transmembrane chemokine CX3CL1, is expressed by neurons and nerve fibers. CX3CR1 + PDAC cell lines migrated in response to human recombinant CX3CL1 and specifically adhered to CX3CL1-expressing cells of neural origin via mechanisms involving activation of G proteins, beta1 integrins, and focal adhesion kinase. In vivo experiments with transplanted PDAC showed that only CX3CR1-transfected tumor cells infiltrated the local peripheral nerves. Immunohistochemistry of CX3CR1 in PDAC specimens revealed that 90% of the samples were positive with a heterogeneous pattern of expression. High receptor score was significantly associated with more prominent tumor perineural infiltration evaluated histologically (P = 0.026). Regression analyses (univariate and multivariate) showed that high CX3CR1 expression and perineural invasion were strongly associated with local and earlier tumor recurrence (P = 0.007). Collectively, this study shows that the CX3CR1 receptor may be involved in PDAC tumor neurotropism and is a relevant and independent risk factor to predict an early local tumor relapse in resected patients. Thus, the CX3CR1-CX3CL1 axis could represent a valuable therapeutic target to prevent tumor perineural dissemination in pancreatic cancer.

Overexpression of fatty acid synthase is associated with palmitoylation of Wnt1 and cytoplasmic stabilization of beta-catenin in prostate cancer.

Fatty acid synthase (FASN), a key metabolic enzyme for liponeogenesis highly expressed in several human cancers, displays oncogenic properties such as resistance to apoptosis and induction of proliferation when overexpressed. To date, no mechanism has been identified to explain the oncogenicity of FASN in prostate cancer. We generated immortalized prostate epithelial cells (iPrECs) overexpressing FASN, and found that (14)C-acetate incorporation into palmitate synthesized de novo by FASN was significantly elevated in immunoprecipitated Wnt-1 when compared to isogenic cells not overexpressing FASN. Overexpression of FASN caused membranous and cytoplasmic beta-catenin protein accumulation and activation, whereas FASN knockdown by short-hairpin RNA resulted in a reduction in the extent of beta-catenin activation. Orthotopic transplantation of iPrECs overexpressing FASN in nude mice resulted in invasive tumors that overexpressed beta-catenin. A strong significant association between FASN and cytoplasmic (stabilized) beta-catenin immunostaining was found in 862 cases of human prostate cancer after computerized subtraction of the membranous beta-catenin signal (P<0.001, Spearman's rho=0.33). We propose that cytoplasmic stabilization of beta-catenin through palmitoylation of Wnt-1 and subsequent activation of the pathway is a potential mechanism of FASN oncogenicity in prostate cancer.