Agent-based approaches have been known to be appropriate as systems and methods in medical administration in recent years. The increased attention to processes led to the recent growth of Business ...Process Management discipline, which quite exclusively adopt discrete-event modeling and simulation. This paper proposes a medical agent-oriented decision support system to integrate the achievements from management science, agent-based modeling, and artificial intelligence. In particular, we performed a practical application concerning a hospital emergency department medical system. We adopt the widely used multi-agent programmable modeling environment NetLogo. First, we demonstrated the ability to perform a clear representation of healthcare processes where agents (i.e., patients and hospital staff) operate in a 3D environment. This model allows performing a traditional
what-if
scenario analysis. Second, we explore how performing intelligent management of patients by applying genetic algorithms to find the criteria for the selection process of the subjects in the admission procedure. The results are encouraging towards a more extensive application of agent-oriented methodologies in healthcare management.
MicroRNAs are being exploited for diagnosis, prognosis and monitoring of cancer and other diseases. Their high tissue specificity and critical role in oncogenesis provide new biomarkers for the ...diagnosis and classification of cancer as well as predicting patients' outcomes. MicroRNAs signatures have been identified for many human tumors, including colorectal cancer (CRC). In most cases, metastatic disease is difficult to predict and to prevent with adequate therapies. The aim of our study was to identify a microRNA signature for metastatic CRC that could predict and differentiate metastatic target organ localization. Normal and cancer tissues of three different groups of CRC patients were analyzed. RNA microarray and TaqMan Array analysis were performed on 66 Italian patients with or without lymph nodes and/or liver recurrences. Data obtained with the two assays were analyzed separately and then intersected to identify a primary CRC metastatic signature. Five differentially expressed microRNAs (hsa-miR-21, -103, -93, -31 and -566) were validated by qRT-PCR on a second group of 16 American metastatic patients. In situ hybridization was performed on the 16 American patients as well as on three distinct commercial tissues microarray (TMA) containing normal adjacent colon, the primary adenocarcinoma, normal and metastatic lymph nodes and liver. Hsa-miRNA-21, -93, and -103 upregulation together with hsa-miR-566 downregulation defined the CRC metastatic signature, while in situ hybridization data identified a lymphonodal invasion profile. We provided the first microRNAs signature that could discriminate between colorectal recurrences to lymph nodes and liver and between colorectal liver metastasis and primary hepatic tumor.
Nowadays, the molecular basis of interaction between low molecular weight compounds and biological macromolecules is the subject of numerous investigations aimed at the rational design of molecules ...with specific therapeutic applications. In the last decades, it has been demonstrated that DNA quadruplexes play a critical role in several biological processes both at telomeric and gene promoting levels thus providing a great stride in the discovery of ligands able to interact with such a biologically relevant DNA conformation. So far, a number of experimental and computational approaches have been successfully employed in order to identify new ligands and to characterize their binding to the DNA. The main focus of this review is the description of these methodologies, placing a particular emphasis on computational methods, isothermal titration calorimetry (ITC), mass spectrometry (MS), nuclear magnetic resonance (NMR), circular dichroism (CD) and fluorescence spectroscopies.
Recent findings have unambiguously demonstrated that DNA G-rich sequences can adopt a G-quadruplex folding in living cells, thus further validating them as crucial targets for anticancer therapy. ...Herein, to identify new potent G4 binders as antitumor drug candidates, we have targeted a 24-nt G4-forming telomeric sequence employing a receptor-based virtual screening approach. Among the best candidates, in vitro binding experiments allowed identification of three novel G4 ligands. Among them, the best compound features an unprecedented binding selectivity for the human telomeric DNA G-quadruplex with no detectable binding for other G4-forming sequences present at different genomic sites. This behavior correlates with the detected ability to generate DNA damage response in tumor cells at the telomeric level and efficient antiproliferative effect on different tumor cell lines at low micromolar concentrations.
This paper focuses on process analysis and computational simulation to address public health management in case of disaster response. By adopting a Business Process Management perspective, we perform ...organization modeling and analysis as a management tool by comparing results from agent-based and discrete event simulations. We focus on the consequences of a mass tragedy, exploiting real data from an Emergency Department after a crowd disaster where people were stamped as a consequence of mass panic. Our models consider activities with corresponding durations, resources as well as patients arrivals based on real data. Finally, once models were validated by managers, simulations can be used to provide suggestions as well as to propose different set of responses to disaster stress in emergency management.
The cross section of 7Be(p,γ)8B represents one of the most important nuclear inputs for the prediction of the high energy component of solar neutrinos and it has also a direct impact on the 7Li ...abundance after the Big Bang Nucleosynthesis. The importance of this reaction triggered an intense experimental work over the last decades, where discrepancies were observed between the results of different measurements. In addition, a question remains about possible common systematic effects, considering that all measurements share the same experimental approach, i.e. an intense proton beam impinging on a 7Be radioactive target. Inverse kinematics, i.e. a 7Be ion beam and a hydrogen target, with the direct measurement of the total reaction cross section by means of the detection of the 8B recoils, can shed light on such systematic effects. Efforts attempted so far were limited by the low 7Be beam intensity. We present here the results of a new measurement at Ecm = 376 to 819 keV using a high intensity 7Be beam in combination with a windowless gas target and the recoil mass separator ERNA (European Recoil mass separator for Nuclear Astrophysics) at CIRCE (Center for Isotopic Research on Cultural and Environmental heritage), Caserta, Italy. Our results, including the systematic error, are compatible with previous measurements that yields lower value of S17(0) and are compatible with the currently accepted value from 1 only at a 2-σ level.
12C+12C reactions are crucial in the evolution of massive stars and explosive scenarios. The measurement of these reactions at astrophysical energies is very challenging due to their extremely small ...cross sections, and the presence of beam induced background originated by the natural 1,2H contaminants in the C targets. In addition, the many discrepancies between different data sets and the complicated resonant structure of the cross sections make the extrapolation to low energies very uncertain. Recently, we performed a direct measurement of the 12C+12C reactions at the CIRCE Laboratory in Italy. Results from a study on target contamination were used, allowing us to measure cross sections at Ec.m. =2.51 − 4.36 MeV with 10-25 keV energy steps. Two stage ΔE-Erest detectors were used for unambiguous particle identification. Branching ratios of individual particle groups were found to vary significantly with energy and angular distributions were also found to be anisotropic, which could be a potential explanation for the discrepancies observed among different data sets.
This paper describes an application of change management in the context of a growing company: the ABC enterprise. The first step of the proposed methodological framework involves the construction of ...the As-is process model, adopting the standard BPMN language. The model is based on an accurate analysis of the data concerning the resources and activities of the company being analyzed, in order to perform a computational simulation of its business processes. After examining existing solutions for business challenges and technological opportunities, several scenarios can be proposed that include possible changes to existing processes. By simulating these scenarios, the results can suggest to analysts useful information to evaluate possible restructuring actions in a quantitative way, comparing the values of an appropriate set of indicators before and after the model’s restructuring.
Susceptibility weighted imaging (SWI) is a relatively new imaging technique. Its high sensitivity to hemorrhagic components and ability to depict microvasculature by means of susceptibility effects ...within the veins allow for the accurate detection, grading, and monitoring of brain tumors. This imaging modality can also detect changes in blood flow to monitor stroke recovery and reveal specific subtypes of vascular malformations. In addition, small punctate lesions can be demonstrated with SWI, suggesting diffuse axonal injury, and the location of these lesions can help predict neurological outcome in patients. This imaging technique is also beneficial for applications in functional neurosurgery given its ability to clearly depict and differentiate deep midbrain nuclei and close submillimeter veins, both of which are necessary for presurgical planning of deep brain stimulation. By exploiting the magnetic susceptibilities of substances within the body, such as deoxyhemoglobin, calcium, and iron, SWI can clearly visualize the vasculature and hemorrhagic components even without the use of contrast agents. The high sensitivity of SWI relative to other imaging techniques in showing tumor vasculature and microhemorrhages suggests that it is an effective imaging modality that provides additional information not shown using conventional MRI. Despite SWI's clinical advantages, its implementation in MRI protocols is still far from consistent in clinical usage. To develop a deeper appreciation for SWI, the authors here review the clinical applications in 4 major fields of neurosurgery: neurooncology, vascular neurosurgery, neurotraumatology, and functional neurosurgery. Finally, they address the limitations of and future perspectives on SWI in neurosurgery.
Through spectral unmixing, hyperspectral imaging (HSI) in fluorescence-guided brain tumor surgery has enabled detection and classification of tumor regions invisible to the human eye. Prior unmixing ...work has focused on determining a minimal set of viable fluorophore spectra known to be present in the brain and effectively reconstructing human data without overfitting. With these endmembers, non-negative least squares regression (NNLS) was used to compute the abundances. However, HSI images are heterogeneous, so one small set of endmember spectra may not fit all pixels well. Additionally, NNLS is the maximum likelihood estimator only if the measurement is normally distributed, and it does not enforce sparsity, which leads to overfitting and unphysical results. Here, we analyzed 555666 HSI fluorescence spectra from 891 ex vivo measurements of patients with brain tumors to show that a Poisson distribution models the measured data 82% better than a Gaussian in terms of the Kullback-Leibler divergence and that the endmember abundance vectors are sparse. With this knowledge, we introduce (1) a library of 9 endmember spectra, (2) a sparse, non-negative Poisson regression algorithm to perform physics-informed unmixing with this library without overfitting, and (3) a highly realistic spectral measurement simulation with known endmember abundances. The new unmixing method was then tested on the human and simulated data and compared to four other candidate methods. It outperforms previous methods with 25% lower error in the computed abundances on the simulated data than NNLS, lower reconstruction error on human data, beUer sparsity, and 31 times faster runtime than state-of-the-art Poisson regression. This method and library of endmember spectra can enable more accurate spectral unmixing to beUer aid the surgeon during brain tumor resection.
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