Strong field gravitational lensing in scalar tensor theories

Strong field gravitational lensing in the Brans-Dicke theory has been studied. The deflection angle for photons passing very close to the photon sphere is estimated for the static spherically symmetric space-time of the theory and the position and magnification of the relativistic images are obtained. Modeling the super massive central object of the galaxy by the Brans-Dicke space-time, numerical values of different strong lensing observable are estimated. It is found that against the expectation there is no significant scalar field effect in the strong field observable lensing parameters. This observation raises question on the potentiality of the strong field lensing to discriminate different gravitational theories.Comment: 20 pages, accepted in Class. Quantum Grav., final versio

Geometrothermodynamics of the Kehagias-Sfetsos Black Hole

The application of information geometric ideas to statistical mechanics using a metric on the space of states, pioneered by Ruppeiner and Weinhold, has proved to be a useful alternative approach to characterizing phase transitions. Some puzzling anomalies become apparent, however, when these methods are applied to the study of black hole thermodynamics. A possible resolution was suggested by Quevedo et al. who emphasized the importance of Legendre invariance in thermodynamic metrics. They found physically consistent results for various black holes when using a Legendre invariant metric, which agreed with a direct determination of the properties of phase transitions from the specific heat. Recently, information geometric methods have been employed by Wei et al. to study the Kehagias-Sfetsos (KS) black hole in Horava-Lifshitz gravity. The formalism suggests that a coupling parameter in this theory plays a role analogous to the charge in Reissner-Nordstrom (RN) black holes or angular momentum in the Kerr black hole and calculation of the specific heat shows a singularity which may be interpreted as a phase transition. When the curvature of the Ruppeiner metric is calculated for such a theory it does not, however, show a singularity at the phase transition point. We show that the curvature of a particular Legendre invariant ("Quevedo") metric for the KS black hole is singular at the phase transition point. We contrast the results for the Ruppeiner, Weinhold and Quevedo metrics and in the latter case investigate the consistency of taking either the entropy or mass as the thermodynamic potential.Comment: v2: some references adde

Enthalpy and the Mechanics of AdS Black Holes

We present geometric derivations of the Smarr formula for static AdS black holes and an expanded first law that includes variations in the cosmological constant. These two results are further related by a scaling argument based on Euler's theorem. The key new ingredient in the constructions is a two-form potential for the static Killing field. Surface integrals of the Killing potential determine the coefficient of the variation of the cosmological constant in the first law. This coefficient is proportional to a finite, effective volume for the region outside the AdS black hole horizon, which can also be interpreted as minus the volume excluded from a spatial slice by the black hole horizon. This effective volume also contributes to the Smarr formula. Since the cosmological constant is naturally thought of as a pressure, the new term in the first law has the form of effective volume times change in pressure that arises in the variation of the enthalpy in classical thermodynamics. This and related arguments suggest that the mass of an AdS black hole should be interpreted as the enthalpy of the spacetime.Comment: 21 pages; v2 references adde

Cell Membrane-Coated Magnetic Nanocubes with a Homotypic Targeting Ability Increase Intracellular Temperature due to ROS Scavenging and Act as a Versatile Theranostic System for Glioblastoma Multiforme

In this study, hybrid nanocubes composed of magnetite (Fe3O4) and manganese dioxide (MnO2), coated with U-251 MG cell-derived membranes (CM-NCubes) are synthesized. The CM-NCubes demonstrate a concentration-dependent oxygen generation (up to 15%), and, for the first time in the literature, an intracellular increase of temperature (6 \ub0C) due to the exothermic scavenging reaction of hydrogen peroxide (H2O2) is showed. Internalization studies demonstrate that the CM-NCubes are internalized much faster and at a higher extent by the homotypic U-251 MG cell line compared to other cerebral cell lines. The ability of the CM-NCubes to cross an in vitro model of the blood-brain barrier is also assessed. The CM-NCubes show the ability to respond to a static magnet and to accumulate in cells even under flowing conditions. Moreover, it is demonstrated that 500 \ub5g mL 121 of sorafenib-loaded or unloaded CM-NCubes are able to induce cell death by apoptosis in U-251 MG spheroids that are used as a tumor model, after their exposure to an alternating magnetic field (AMF). Finally, it is shown that the combination of sorafenib and AMF induces a higher enzymatic activity of caspase 3 and caspase 9, probably due to an increment in reactive oxygen species by means of hyperthermia

Black Holes in Ho\v{r}ava Gravity with Higher Derivative Magnetic Terms

We consider Horava gravity coupled to Maxwell and higher derivative magnetic terms. We construct static spherically symmetric black hole solutions in the low-energy approximation. We calculate the horizon locations and temperatures in the near-extremal limit, for asymptotically flat and (anti-)de Sitter spaces. We also construct a detailed balanced version of the theory, for which we find projectable and non-projectable, non-perturbative solutions.Comment: 17 pages. v2: Up to date with published version; some minor remarks and more reference

Potentially inappropriate medication in older participants of the Berlin Aging Study II (BASE-II) - Sex differences and associations with morbidity and medication use

INTRODUCTION: Multimorbidity in advanced age and the need for drug treatment may lead to polypharmacy, while pharmacokinetic and pharmacodynamic changes may increase the risk of adverse drug events (ADEs). OBJECTIVE: The aim of this study was to determine the proportion of subjects using potentially inappropriate medication (PIM) in a cohort of older and predominantly healthy adults in relation to polypharmacy and morbidity. METHODS: Cross-sectional data were available from 1,382 study participants (median age 69 years, IQR 67-71, 51.3% females) of the Berlin Aging Study II (BASE-II). PIM was classified according to the EU(7)-PIM and German PRISCUS (representing a subset of the former) list. Polypharmacy was defined as the concomitant use of at least five drugs. A morbidity index (MI) largely based on the Charlson Index was applied to evaluate the morbidity burden. RESULTS: Overall, 24.1% of the participants were affected by polypharmacy. On average, men used 2 (IQR 1-4) and women 3 drugs (IQR 1-5). According to PRISCUS and EU(7)-PIM, 5.9% and 22.6% of participants received at least one PIM, while use was significantly more prevalent in females (25.5%) compared to males (19.6%) considering EU(7)-PIM (p = 0.01). In addition, morbidity in males receiving PIM according to EU(7)-PIM was higher (median MI 1, IQR 1-3) compared to males without PIM use (median MI 1, IQR 0-2, p<0.001). CONCLUSION: PIM use occurred more frequently in women than in men, while it was associated with higher morbidity in males. As expected, EU(7)-PIM identifies more subjects as PIM users than the PRISCUS list but further studies are needed to investigate the differential impact of both lists on ADEs and outcome. KEY POINTS: We found PIM use to be associated with a higher number of regular medications and with increased morbidity. Additionally, we detected a higher prevalence of PIM use in females compared to males, suggesting that women and people needing intensive drug treatment are patient groups, who are particularly affected by PIM use

Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset

<p>Abstract</p> <p>Background</p> <p>Inferring gene regulatory networks from data requires the development of algorithms devoted to structure extraction. When only static data are available, gene interactions may be modelled by a Bayesian Network (BN) that represents the presence of direct interactions from regulators to regulees by conditional probability distributions. We used enhanced evolutionary algorithms to stochastically evolve a set of candidate BN structures and found the model that best fits data without prior knowledge.</p> <p>Results</p> <p>We proposed various evolutionary strategies suitable for the task and tested our choices using simulated data drawn from a given bio-realistic network of 35 nodes, the so-called insulin network, which has been used in the literature for benchmarking. We assessed the inferred models against this reference to obtain statistical performance results. We then compared performances of evolutionary algorithms using two kinds of recombination operators that operate at different scales in the graphs. We introduced a niching strategy that reinforces diversity through the population and avoided trapping of the algorithm in one local minimum in the early steps of learning. We show the limited effect of the mutation operator when niching is applied. Finally, we compared our best evolutionary approach with various well known learning algorithms (MCMC, K2, greedy search, TPDA, MMHC) devoted to BN structure learning.</p> <p>Conclusion</p> <p>We studied the behaviour of an evolutionary approach enhanced by niching for the learning of gene regulatory networks with BN. We show that this approach outperforms classical structure learning methods in elucidating the original model. These results were obtained for the learning of a bio-realistic network and, more importantly, on various small datasets. This is a suitable approach for learning transcriptional regulatory networks from real datasets without prior knowledge.</p

C3-Cloud personalised care plan development platform for addressing the needs of multi-morbidity and managing poly-pharmacy : protocol for a pilot technology trial

Background: There is an increasing need to organise the care around the patient and not the disease, as well as taking into account the complex realities of multiple physical, psycho-social conditions and polypharmacy. Integrated patient-centred care delivery platforms have been developed for both patients and clinicians. These platforms could provide a promising way to achieve a collaborative environment that improves the provision of integrated care for patients via enhanced ICT solutions. Objective: The C3-Cloud project has developed two collaborative computer platforms for patients and members of the Multi-Disciplinary Team and deployed these in three different European settings. The objective of this study is to pilot test the platforms and evaluate their impact on patients, informal caregivers, healthcare professionals and, in extend, healthcare systems. Methods: This paper describes the protocol for conducting an evaluation of the user-centred design, user experience, acceptability, and usefulness of the platforms. For this, four ‘testing and evaluation’ phases have been defined, involving multiple qualitative methods, and advanced impact modelling. Results: The technology trial in this 4-year funded project (2016-2020) is currently in its execution phase. The testing and evaluation phase 1 and 2 have been completed with satisfying results on system component tests, and promising results on application and usability tests. The pilot technology trial for evaluation phase 3 and 4 was launched in August 2019. Data collection for these phases is underway and results are forthcoming, approximately in April 2020. We believe that the phased, iterative approach taken is useful as it involves relevant stakeholders at crucial stages in the platform development and allows for a sound user acceptance assessment of the final product. Conclusions: Patients with multiple chronic conditions often experience shortcomings in the care they receive. It is hoped that personalised care plan platforms for patients and collaboration platforms for members of Multi-Disciplinary Teams can help to tackle the specific challenges of clinical guideline reconciliation for multimorbid patients and improved the management of poly-pharmacy. The initial evaluative phases have indicated promising results of platform usability. The phased methodology has shown useful results in the first two phases, while results of phase 3 and 4 are pending. Clinical Trial: https://www.clinicaltrials.gov/ct2/show/NCT0383420

Global and decomposition evolutionary support vector machine approaches for time series forecasting

Multi-step ahead Time Series Forecasting (TSF) is a key tool for support- ing tactical decisions (e.g., planning resources). Recently, the support vector machine emerged as a natural solution for TSF due to its nonlinear learning capabilities. This paper presents two novel Evolutionary Support Vector Machine (ESVM) methods for multi-step TSF. Both methods are based on an Estimation Distribution Algorithm (EDA) search engine that automatically performs a simultaneous variable (number of inputs) and model (hyperparameters) selection. The Global ESVM (GESVM) uses all past patterns to fit the support vector machine, while the Decomposition ESVM (DESVM) separates the series into trended and stationary effects, using a distinct ESVM to forecast each effect and then summing both predictions into a sin- gle response. Several experiments were held, using six time series. The proposed approaches were analyzed under two criteria and compared against a recent Evolu- tionary Artificial Neural Network (EANN) and two classical forecasting methods, Holt-Winters and ARIMA. Overall, the DESVM and GESVM obtained competitive and high quality results. Furthermore, both ESVM approaches consume much less computational effort when compared with EANN.The authors wish to thank Ramon Sagarna for introducing the subject of EDA. The work of P. Cortez was supported by FEDER (program COMPETE and FCT) under project FCOMP-01-0124-FEDER-022674

Treatment challenges in and outside a specialist network setting: Pancreatic neuroendocrine tumours

Pancreatic Neuroendocrine Neoplasms comprise a group of rare tumours with special biology, an often indolent behaviour and particular diagnostic and therapeutic requirements. The specialized biochemical tests and radiological investigations, the complexity of surgical options and the variety of medical treatments that require individual tailoring, mandate a multidisciplinary approach that can be optimally achieved through an organized network. The present study describes currents concepts in the management of these tumours as well as an insight into the challenges of delivering the pathway in and outside a Network