An expression signature of the angiogenic response in gastrointestinal neuroendocrine tumours: correlation with tumour phenotype and survival outcomes.

BACKGROUND: Gastroenteropancreatic neuroendocrine tumours (GEP-NETs) are heterogeneous with respect to biological behaviour and prognosis. As angiogenesis is a renowned pathogenic hallmark as well as a therapeutic target, we aimed to investigate the prognostic and clinico-pathological role of tissue markers of hypoxia and angiogenesis in GEP-NETs. METHODS: Tissue microarray (TMA) blocks were constructed with 86 tumours diagnosed from 1988 to 2010. Tissue microarray sections were immunostained for hypoxia inducible factor 1α (Hif-1α), vascular endothelial growth factor-A (VEGF-A), carbonic anhydrase IX (Ca-IX) and somatostatin receptors (SSTR) 1–5, Ki-67 and CD31. Biomarker expression was correlated with clinico-pathological variables and tested for survival prediction using Kaplan–Meier and Cox regression methods. RESULTS: Eighty-six consecutive cases were included: 51% male, median age 51 (range 16–82), 68% presenting with a pancreatic primary, 95% well differentiated, 51% metastatic. Higher grading (P=0.03), advanced stage (P<0.001), high Hif-1α and low SSTR-2 expression (P=0.03) predicted for shorter overall survival (OS) on univariate analyses. Stage, SSTR-2 and Hif-1α expression were confirmed as multivariate predictors of OS. Median OS for patients with SSTR-2+/Hif-1α-tumours was not reached after median follow up of 8.8 years, whereas SSTR-2-/Hif-1α+ GEP-NETs had a median survival of only 4.2 years (P=0.006). CONCLUSION: We have identified a coherent expression signature by immunohistochemistry that can be used for patient stratification and to optimise treatment decisions in GEP-NETs independently from stage and grading. Tumours with preserved SSTR-2 and low Hif-1α expression have an indolent phenotype and may be offered less aggressive management and less stringent follow up

Neuronal chemotaxis by optically manipulated liposomes

We probe chemotaxis of single neurons, induced by signalling molecules which were optically delivered from liposomes in the neighbourhood of the cells. We implemented an optical tweezers setup combined with a micro-dissection system on an inverted microscope platform. Molecules of Netrin-1 protein were encapsulated into micron-sized liposomes and manipulated to micrometric distances from a specific growth cone of a hippocampal neuron by the IR optical tweezers. The molecules were then released broken the liposomes with UV laser pulses. Chemotaxis induced by the delivered molecules was confirmed by the migration of the growth cone toward the liposome position. Since the delivery can be manipulated with high temporal and spatial resolution and the number of molecules released can be controlled quite precisely by tuning the liposome size and the solution concentration, this technique opens new opportunities to investigate the effect of physiological active compounds as Netrin-1 to neuronal signalling and guidance, which represents an important issue in neurobiology

Italian Oncological Pain Survey (IOPS) A Multicentre Italian Study of Breakthrough Pain Performed in Different Settings

Objective: A survey of breakthrough pain (BTP) was performed in five palliative care units (PCU), seven oncology departments (ONC), and nine pain clinics (OPC). Methods: A standard algorithm was used to confirm the diagnosis of BTP of patients refereed to different settings. Results: 1,412 evaluable cancer patients were enrolled. 53.9% were males and the mean age was 63.7±13.1 years. The mean intensity of background pain was 2.8±0.73. Patients reported 2.4±1.1 BTP episodes/day with a mean intensity of 7.37±1.28. 80.6% patients reported that the BTP had a significant negative impact in everyday life. The majority of patients reported a fast onset of BTP, which was predictable in 50.7% of cases, while BTP with a gradual onset (>10 min) was less predictable (29%) (P=0.001). PCU patients were older, had lower Karnofsky levels, a lower number of BTP episodes/day, a slow onset of BTP onset, and a less predictable BTP. Cancer diagnosis was performed a mean of 23.5 months (SD±32.8) before the assessment. The mean duration of background pain was 3.5 months (SD±3.5), and the mean duration of any analgesic treatment was 2.5 months (SD±3). BTP started a mean of 2.2 months (SD±1.9) before the assessment. Characteristics of BTP were influenced by the course of disease, as well as the duration of background pain and initiation of BTP. Most patients took rapid onset opioids and were satisfied with the treatment. BTP diagnosis was prevalently made by ONC and OPC physicians, and rarely by GPs. Conclusion: This survey performed by an Italian observatory expert review group, has confirmed that the BTP represents a clinically relevant condition with a negative impact on the patient’s quality of life. BTP was detected in all settings involved. A number of factors are associated with the BTP. Also factors regarding the course of disease and setting of care have been assessed. This information may help in stratifying patients or predicting the risk of development of BTP with specific characteristics

Developing an online predictor to predict product sulfur concentration for HDS unit

Hydrodesulfurization (HDS) is an important process in refining industries. Advanced control system (e.g. model predictive controller) requires on-line measurement of the product sulfur at the reactor outlet. However, most HDS processes do not have a sulfur analyzer at the reactor outlet. In order to predict product sulfur concentration usually a data based sulfur predictor is developed. Performance of data based predictor is usually poor since some of the input parameters (e.g. feed sulfur concentration) are unknown. The objective of this thesis is to overcome these limitations of data based predictors and develop an online product sulfur predictor for HDS unit. In this thesis, a hybrid model is proposed, developed and validated (using industrial data), which could predict product sulfur concentration for online HDS system. The proposed hybrid structure is a combination of a reaction kinetics based HDS reactor model and an empirical model based on support vector regression (SVR). The mechanistic model runs in off-line mode to estimate the feed sulfur concentration while the data based model uses the estimated feed sulfur concentration and other process variables to predict the product sulfur concentration. The predicted sulfur concentration can be compared with the lab measurements or sulfur analyzer located further downstream of the process at the tankage. In case there is a large discrepancy, the predictor goes to a calibration mode and uses the mechanistic model to re-estimate the feed sulfur concentration. The detailed logic for the online prediction is also developed. Finally a Matlab based Graphical User Interface (GUI) has been developed for the hybrid sulfur predictor for easy implementation to any HDS process

Less than 5 Netrin-1 molecules initiate attraction but 200 Sema3A molecules are necessary for repulsion

Guidance molecules, such as Sema3A or Netrin-1, induce growth cone (GC) repulsion or attraction. In order to determine the speed of action and efficiency of these guidance cues we developed an experimental procedure to deliver controlled amounts of these molecules. Lipid vesicles encapsulating 10-10 4 molecules of Sema3A or Netrin-1 were manipulated with high spatial and temporal resolution by optical tweezers and their photolysis triggered by laser pulses. Guidance molecules released from the vesicles diffused and reached the GC membrane in a few seconds. Following their arrival, GCs retracted or grew in 20-120 s. By determining the number of guidance molecules trapped inside vesicles and estimating the fraction of guidance molecules reaching the GC, we show that the arrival of less than 5 Netrin-1 molecules on the GC membrane is sufficient to induce growth. In contrast, the arrival of about 200 Sema3A molecules is necessary to induce filopodia repulsion