Can a microscopic stochastic model explain the emergence of pain cycles in patients?

A stochastic model is here introduced to investigate the molecular mechanisms which trigger the perception of pain. The action of analgesic drug compounds is discussed in a dynamical context, where the competition with inactive species is explicitly accounted for. Finite size effects inevitably perturb the mean-field dynamics: Oscillations in the amount of bound receptors spontaneously manifest, driven by the noise which is intrinsic to the system under scrutiny. These effects are investigated both numerically, via stochastic simulations and analytically, through a large-size expansion. The claim that our findings could provide a consistent interpretative framework to explain the emergence of cyclic behaviors in response to analgesic treatments, is substantiated.Comment: J. Stat. Mech. (Proceedings UPON2008

Stochastic Turing Patterns on a Network

The process of stochastic Turing instability on a network is discussed for a specific case study, the stochastic Brusselator model. The system is shown to spontaneously differentiate into activator-rich and activator-poor nodes, outside the region of parameters classically deputed to the deterministic Turing instability. This phenomenon, as revealed by direct stochastic simulations, is explained analytically, and eventually traced back to the finite size corrections stemming from the inherent graininess of the scrutinized medium.Comment: The movies referred to in the paper are provided upon request. Please send your requests to Duccio Fanelli ([email protected]) or Francesca Di Patti ([email protected]

Non-Gaussian fluctuations in stochastic models with absorbing barriers

The dynamics of a one-dimensional stochastic model is studied in presence of an absorbing boundary. The distribution of fluctuations is analytically characterized within the generalized van Kampen expansion, accounting for higher order corrections beyond the conventional Gaussian approximation. The theory is shown to successfully capture the non Gaussian traits of the sought distribution returning an excellent agreement with the simulations, for {\it all times} and arbitrarily {\it close} to the absorbing barrier. At large times, a compact analytical solution for the distribution of fluctuations is also obtained, bridging the gap with previous investigations, within the van Kampen picture and without resorting to alternative strategies, as elsewhere hypothesized.Comment: 2 figures, submitted to Phys. Rev. Let

heat exchanger design and optimization by using genetic algorithm for externally fired micro turbine

Abstract In this study, a new configuration where syngas produced by downdraft gasifier is feed directly in an externally fired air turbine is discussed. Attention was posed towards the critical component of this configuration: the heat exchanger. To achieve acceptable electrical efficiencies, high temperature of the air at the inlet turbine section was imposed. A code for heat exchanger design was built by using Matlab®, while the geometrical optimization was performed by using modeFRONTIER® by imposing a multi-objective function to maximize the overall heat transfer coefficient and minimize both costs and pressure drops across the equipment

Insights for the future of health system partnerships in low- and middle-income countries: a systematic literature review

BACKGROUND: Despite growing support for the private sector involvement in the provision of public health services in Low- and Middle-Income Countries (LMICs), a lack of clear information on the future of the provision of such services restricts the ability of managers and policy-makers to assess how feasible integration between public and private actors may be in these countries. This paper presents a systematic literature review which traces the dynamics and boundaries of public-private partnerships for the healthcare sector in LMICs. METHODS: A total of 723 articles indexed in Scopus were initially submitted to bibliometric analysis. Finally, 148 articles published in several academic journals were selected for independent full-text review by two researchers. Content analysis was made in order to minimise mistakes in interpreting the findings of studies in the sample. RESULTS: Public-private partnerships identified through the content analysis were categorised into four research areas: 1) Transfer of resources; 2) Co-production of health goods and services; 3) Governance networks; 4) Criteria for successful partnership development. CONCLUSIONS: The four main research areas supply suggestions for a future research agenda, and managerial and policy implications for partnerships in LMICs

Antibacterial activity of matrix-bound ovotransferrin

Ovotransferrin immobilized by covalent linkage to Sepharose 4B showed a bacteriostatic effect towards Escherichia coli similar to that of free ovotransferrin. The growth of the bacteria, after exposure to the gel-bound ovotransferrin and its removal, depended on the length of exposure. The results suggest that the antibacterial activity of transferrin is not due simply to the removal of iron from the medium

Intrinsic noise and discrete-time processes

A general formalism is developed to construct a Markov chain model that converges to a one-dimensional map in the infinite population limit. Stochastic fluctuations are therefore internal to the system and not externally specified. For finite populations an approximate Gaussian scheme is devised to describe the stochastic fluctuations in the non-chaotic regime. More generally, the stochastic dynamics can be captured using a stochastic difference equation, derived through an approximation to the Markov chain. The scheme is demonstrated using the logistic map as a case study.Comment: Modified version accepted for publication in Phys. Rev. E Rapid Communications. New figures adde

Stochastic Turing patterns in the Brusselator model

A stochastic version of the Brusselator model is proposed and studied via the system size expansion. The mean-field equations are derived and shown to yield to organized Turing patterns within a specific parameters region. When determining the Turing condition for instability, we pay particular attention to the role of cross diffusive terms, often neglected in the heuristic derivation of reaction diffusion schemes. Stochastic fluctuations are shown to give rise to spatially ordered solutions, sharing the same quantitative characteristic of the mean-field based Turing scenario, in term of excited wavelengths. Interestingly, the region of parameter yielding to the stochastic self-organization is wider than that determined via the conventional Turing approach, suggesting that the condition for spatial order to appear can be less stringent than customarily believed.Comment: modified version submitted to Phys Rev. E. 5. 3 Figures (5 panels) adde

Vascular Patterns in Cutaneous Ulcerated Basal Cell Carcinoma: A Retrospective Blinded Study Including Dermoscopy.

Abstract The aim of this retrospective study was to determine the type and prevalence of vascular patterns in the ulcerated and non-ulcerated portions of histologically proven basal cell carcinomas (BCCs) and correlate them with other dermoscopic and clinical features, including the clinically supposed diagnosis. Three authors retrospectively collected 156 clinical and 156 dermoscopic digital images of ulcerated BCCs (histologically confirmed); each image was blindly evaluated by 2 other authors, who did not know the histological diagnosis. Seventeen lesions were completely ulcerated, while 139 lesions presented ulcerated and non-ulcerated portions. Correct clinical diagnosis was associated with the type of lesion, in particular 90.6% of partially ulcerated lesions were correctly diagnosed with clinical-dermoscopic examination, compared with 11.8% of totally ulcerated lesions (χ2 = 64.00, p = 0.000). Presence of arborizing pattern in the ulcerated portion was associated with a correct diagnosis (Fisher's exact test, p = 0.015). Correct diagnosis was also associated with absence of dotted pattern in the non-ulcerated area (χ2 = 16.18, p = 0.000); the absence of hairpin (χ2 = 6.08, p = 0.000) and glomerular patterns were associated with correct diagnosis in the ulcerated areas (χ2 = 18.64, p = 0.000). In case of completely ulcerated BCC the clinician lacks the means to correctly identify the correct nature of the lesion, and is driven towards an incorrect diagnostic conclusion

Decipher the glioblastoma microenvironment: The first milestone for new groundbreaking therapeutic strategies

Glioblastoma (GBM) is the most common primary malignant brain tumour in adults. Despite the combination of novel therapeutical approaches, it remains a deadly malignancy with an abysmal prognosis. GBM is a polymorphic tumour from both molecular and histological points of view. It consists of different malignant cells and various stromal cells, contributing to tumour initiation, progression, and treatment response. GBM’s microenvironment is multifaceted and is made up of soluble factors, extracellular matrix components, tissue-resident cell types (e.g., neurons, astrocytes, endothelial cells, pericytes, and fibroblasts) together with resident (e.g., microglia) or recruited (e.g., bone marrow-derived macrophages) immune cells. These latter constitute the so-called immune microenvironment, accounting for a substantial GBM’s tumour volume. Despite the abundance of immune cells, an intense state of tumour immunosuppression is promoted and developed; this represents the significant challenge for cancer cells’ immune-mediated destruction. Though literature data suggest that distinct GBM’s subtypes harbour differences in their microenvironment, its role in treatment response remains obscure. However, an in-depth investigation of GBM’s microenvironment may lead to novel therapeutic opportunities to improve patients’ outcomes. This review will elucidate the GBM’s microenvironment composition, highlighting the current state of the art in immunotherapy approaches. We will focus on novel strategies of active and passive immunotherapies, including vaccination, gene therapy, checkpoint blockade, and adoptive T-cell therapies