Toward the molecular dissection of peritoneal pseudomyxoma.

BACKGROUND: Outcome of pseudomyxoma peritonei (PMP) after cytoreductive surgery (CRS) and hypertermic intraperitoneal chemotherapy (HIPEC) is heterogeneous even after adjusting for clinico-pathological prognostic variables. The identification of additional prognostic or even predictive biomarkers is an unmet clinical need. PATIENTS AND METHODS: Forty patients with mucinous appendiceal tumors and PMP were clinically eligible and had evaluable tumor samples obtained after CRS and HIPEC. We carried out next-generations sequencing (NGS) of 50 gene's hotspot regions contained in the Hotspot Cancer Panel v2 using the Ion Torrent Personal Genome Machine platform (Life Technologies). RESULTS: KRAS and GNAS mutations were found in 72% and 52%, and their allelic frequency was below 10% in 55% and 43% of samples, respectively. KRAS and GNAS mutations were associated with worse progression-free survival (PFS) at univariate analysis (P = 0.006 and 0.011, respectively). At multivariate analysis, only KRAS mutations were independently associated with PFS (P = 0.012); GNAS mutations were not-being significantly associated with other poor prognostic features such as incomplete cytoreduction or KRAS mutations. Validation of results was carried out in an independent bi-institutional cohort of 25 patients and the prognostic effect of KRAS mutations was again confirmed in the multivariate model (P = 0.029). NGS approach allowed the discovery of other potentially druggable mutations such as those in PI3K, AKT, LKB1, FGFR3 and PDGFRA. CONCLUSIONS: Given the homogeneity of this series and the sensitivity of NGS in this low-cellularity tumor, we demonstrated for the first time a poor prognostic role of KRAS mutations.

Hybrid x-space: a new approach for MPI reconstruction.

Magnetic particle imaging (MPI) is a new medical imaging technique capable of recovering the distribution of superparamagnetic particles from their measured induced signals. In literature there are two main MPI reconstruction techniques: measurement-based (MB) and x-space (XS). The MB method is expensive because it requires a long calibration procedure as well as a reconstruction phase that can be numerically costly. On the other side, the XS method is simpler than MB but the exact knowledge of the field free point (FFP) motion is essential for its implementation. Our simulation work focuses on the implementation of a new approach for MPI reconstruction: it is called hybrid x-space (HXS), representing a combination of the previous methods. Specifically, our approach is based on XS reconstruction because it requires the knowledge of the FFP position and velocity at each time instant. The difference with respect to the original XS formulation is how the FFP velocity is computed: we estimate it from the experimental measurements of the calibration scans, typical of the MB approach. Moreover, a compressive sensing technique is applied in order to reduce the calibration time, setting a fewer number of sampling positions. Simulations highlight that HXS and XS methods give similar results. Furthermore, an appropriate use of compressive sensing is crucial for obtaining a good balance between time reduction and reconstructed image quality. Our proposal is suitable for open geometry configurations of human size devices, where incidental factors could make the currents, the fields and the FFP trajectory irregular.

Formation of the folding nucleus of an SH3 domain investigated by loosely coupled molecular dynamics simulations.

The experimentally well-established folding mechanism of the src-SH3 domain, and in particular the phi-value analysis of its transition state, represents a sort of testing table for computational investigations of protein folding. Here, parallel molecular dynamics simulations of the src-SH3 domain have been performed starting from denatured conformations. By rescuing and restarting only trajectories approaching the folding transition state, an ensemble of conformations was obtained with a completely structured central beta-sheet and a native-like packing of residues Ile-110, Ala-121, and Ile-132. An analysis of the trajectories shows that there are several pathways leading to the formation of the central beta-sheet whereas its two hairpins form in a different but consistent way.

Role of native-state topology in the stabilization of intracellular antibodies.

The role played by the geometric position of each amino acid in the folding process of the immunoglobulin (Ig) variable domain is identified and measured through molecular dynamics simulations of models based on the topology of its native state. This measure allows identifying the parts of the protein that, for geometrical reasons, when mutated, would result in relevant protein stability changes. Simulations were performed without considering the covalent disulfide bond present in most of the Ig domains. The results are in good agreement with site-directed mutagenesis experiments on the folding of intracellular antibodies in which the disulfide bond does not form. We also found agreement with data on amino acid conservation in the Ig variable domain sequences. This indicates a new way for a rational approach to the design of intracellular antibodies more resistant to the suppression of the disulfide bond that occurs in the cytoplasm.

Analytical model for the effects of learning on spike count distributions.

The spike count distribution observed when recording from a variety of neurons in many different conditions has a fairly stereotypical shape, with a single mode at zero or close to a low average count, and a long, quasi-exponential tail to high counts. Such a distribution has been suggested to be the direct result of three simple facts: the firing frequency of a typical cortical neuron is close to linear in the summed input current entering the soma, above a threshold; the input current varies on several timescales, both faster and slower than the window used to count spikes; and the input distribution at any timescale can be taken to be approximately normal. The third assumption is violated by associative learning, which generates correlations between the synaptic weight vector on the dendritic tree of a neuron, and the input activity vectors it is repeatedly subject to. We show analytically that for a simple feed-forward model, the normal distribution of the slow components of the input current becomes the sum of two quasi-normal terms. The term important below threshold shifts with learning, while the term important above threshold does not shift but grows in width. These deviations from the standard distribution may be observable in appropriate recording experiments.