Diffuse soil CO2 degassing from Linosa island

Herein, we present and discuss the result of 148 measurements of soil CO2 flux performed for the first time in Linosa island (Sicily Channel, Italy), a Plio-Pleistocene volcanic complex no longer active but still of interest owing to its location within a seismically active portion of the Sicily Channel rift system. The main purpose of this survey was to assess the occurrence of CO2 soil degassing, and compare flux estimations from this island with data of soil degassing from worldwide active volcanic as well as non-volcanic areas. To this aim soil CO2 fluxes were measured over a surface of about 4.2 km2 covering ~80% of the island. The soil CO2 degassing was observed to be mainly concentrated in the eastern part of the island likely due to volcano-tectonic lineaments, the presence of which is in good agreement with the known predominant regional faults system. Then, the collected data were interpreted using sequential Gaussian simulation that allowed estimating the total CO2 emissions of the island. Results show low levels of CO2 emissions from the soil of the island (~55 ton d-1) compared with CO2 emissions of currently active volcanic areas, such as Miyakejima (Japan) and Vulcano (Italy). Results from this study suggest that soil degassing in Linosa is mainly fed by superficial organic activity with a moderate contribution of a deep CO2 likely driven by NWSE trending active tectonic structures in the eastern part of the island

Statistics of electromagnetic transitions as a signature of chaos in many-electron atoms

Using a configuration interaction approach we study statistics of the dipole matrix elements (E1 amplitudes) between the 14 lower odd states with J=4 and 21st to 100th even states with J=4 in the Ce atom (1120 lines). We show that the distribution of the matrix elements is close to Gaussian, although the width of the Gaussian distribution, i.e. the root-mean-square matrix element, changes with the excitation energy. The corresponding line strengths are distributed according to the Porter-Thomas law which describes statistics of transition strengths between chaotic states in compound nuclei. We also show how to use a statistical theory to calculate mean squared values of the matrix elements or transition amplitudes between chaotic many-body states. We draw some support for our conclusions from the analysis of the 228 experimental line strengths in Ce [J. Opt. Soc. Am. v. 8, p. 1545 (1991)], although direct comparison with the calculations is impeded by incompleteness of the experimental data. Nevertheless, the statistics observed evidence that highly excited many-electron states in atoms are indeed chaotic.Comment: 16 pages, REVTEX, 4 PostScript figures (submitted to Phys Rev A

Study of a constrained finite element elbow prosthesis: the influence of the implant placement

Background: The functional results of total elbow arthroplasty (TEA) are controversial and the medium- to long-term revision rates are relatively high. The aim of the present study was to analyze the stresses of TEA in its classic configuration, identify the areas of greatest stress in the prosthesis–bone–cement interface, and evaluate the most wearing working conditions. Materials and methods: By means of a reverse engineering process and using a 3D laser scanner, CAD (computer-aided drafting) models of a constrained elbow prosthesis were acquired. These CAD models were developed and their elastic properties, resistance, and stresses were studied through finite element analysis (finite element method—FEM). The obtained 3D elbow-prosthesis model was then evaluated in cyclic flexion–extension movements (> 10 million cycles). We highlighted the configuration of the angle at which the highest stresses and the areas most at risk of implant mobilization develop. Finally, we performed a quantitative study of the stress state after varying the positioning of the stem of the ulnar component in the sagittal plane by ± 3°. Results: The greatest von Mises stress state in the bone component for the 90° working configuration was 3.1635 MPa, which occurred in the most proximal portion of the humeral blade and in the proximal middle third of the shaft. At the ulnar level, peaks of 4.1763 MPa were recorded at the proximal coronoid/metaepiphysis level. The minimum elastic resistance and therefore the greatest stress states were recorded in the bone region at the apex of the ulnar stem (0.001967 MPa). The results of the analysis for the working configurations at 0° and 145° showed significant reductions in the stress states for both prosthetic components; similarly, varying the positioning of the ulnar component at 90° (− 3° in the sagittal plane, 0° in the frontal plane) resulted in better working conditions with a greater resulting developed force and a lower stress peak in the ulnar cement. Conclusion: The areas of greatest stress occur in specific regions of the ulnar and humeral components at the bone–cement–prosthesis interface. The heaviest configuration in terms of stresses was when the elbow was flexed at 90°. Variations in the positioning in the sagittal plane can mechanically affect the movement, possibly resulting in longer survival of the implant. Level of evidence:

Aggregation Prediction in Therapeutic Protein Formulations for Excipient Design

Computational Infrastructure & Informatics Poster SessionA major concern in the development therapeutic protein formulations is protein aggregation. Proteins can interact to form bound groups of protein molecules or aggregates. Aggregates in protein formulations reduce effectiveness and can lead to severe immune responses in patients. Excipients are additive molecules that are not therapeutically active, but can increase the stability of protein formulations. An ideal excipient binds with aggregation prone regions on the protein to limit interaction of that region with another protein molecule. The goal of this project is to predict aggregation prone regions and design excipients to interact with these regions. Several tools exist to predict which regions on a protein will be most likely to initiate aggregation. Aggrescan (http://bioinf.uab.es/aggrescan/) and SAP (Spatial Aggregation Potential) were used to predict aggregation prone regions on proteins and the results were compared. Aggrescan uses experimental data to assign each amino acid an aggregation propensity score. An aggregation prone region is identified by a sequence of amino acids with high propensities. The three-dimensional structure is not used in the aggregation prediction. SAP uses molecular simulation to determine regions that are hydrophobic and solvent accessible. Each residue is scored and the results are mapped to the three-dimensional protein structure. A successful prediction tool must use parameters that correlate with aggregation potential for a folded protein. The aggregation prone regions predicted by Aggrescan and SAP were compared to experimental data on protein aggregation. Proteins with a high number of predicted regions or large predicted regions were found to have higher experimental percent aggregation. With the regions identified, molecular simulations were performed for protein-excipient systems. A protein and small molecule docking algorithm was used to determine which regions of the protein certain excipients interacted with. Trehalose, poly(vinylpyrrolidone), and guanadine hydrochloride were used. For an excipient to successfully stabilize a protein and prevent aggregation, the excipient should interact with the aggregation prone regions predicted by Aggrescan and SAP. The predicted regions were compared to the regions where the excipient docks in the molecular simulation. The simulation results were compared to experimental data on the percent aggregation observed in several protein-excipient formulations. The excipients that were found to interact with the predicted aggregation prone regions in simulations should also experimentally prohibit aggregation, leading to lower percent aggregation. Hydrogen-deuterium swapping along with FTIR analysis will be performed experimentally to determine exposed regions on the protein. Proteins with a high number of exposed regions are less stable. The exposed regions will be compared to the aggregation prone regions predicted by Aggrescan and SAP

Results of the IGEC-2 search for gravitational wave bursts during 2005

The network of resonant bar detectors of gravitational waves resumed coordinated observations within the International Gravitational Event Collaboration (IGEC-2). Four detectors are taking part in this collaboration: ALLEGRO, AURIGA, EXPLORER and NAUTILUS. We present here the results of the search for gravitational wave bursts over 6 months during 2005, when IGEC-2 was the only gravitational wave observatory in operation. The network data analysis implemented is based on a time coincidence search among AURIGA, EXPLORER and NAUTILUS, keeping the data from ALLEGRO for follow-up studies. With respect to the previous IGEC 1997-2000 observations, the amplitude sensitivity of the detectors to bursts improved by a factor about 3 and the sensitivity bandwidths are wider, so that the data analysis was tuned considering a larger class of detectable waveforms. Thanks to the higher duty cycles of the single detectors, we decided to focus the analysis on three-fold observation, so to ensure the identification of any single candidate of gravitational waves (gw) with high statistical confidence. The achieved false detection rate is as low as 1 per century. No candidates were found.Comment: 10 pages, to be submitted to Phys. Rev.

Statistical properties of power-law random banded unitary matrices in the delocalization-localization transition regime

Power-law random banded unitary matrices (PRBUM), whose matrix elements decay in a power-law fashion, were recently proposed to model the critical statistics of the Floquet eigenstates of periodically driven quantum systems. In this work, we numerically study in detail the statistical properties of PRBUM ensembles in the delocalization-localization transition regime. In particular, implications of the delocalization-localization transition for the fractal dimension of the eigenvectors, for the distribution function of the eigenvector components, and for the nearest neighbor spacing statistics of the eigenphases are examined. On the one hand, our results further indicate that a PRBUM ensemble can serve as a unitary analog of the power-law random Hermitian matrix model for Anderson transition. On the other hand, some statistical features unseen before are found from PRBUM. For example, the dependence of the fractal dimension of the eigenvectors of PRBUM upon one ensemble parameter displays features that are quite different from that for the power-law random Hermitian matrix model. Furthermore, in the time-reversal symmetric case the nearest neighbor spacing distribution of PRBUM eigenphases is found to obey a semi-Poisson distribution for a broad range, but display an anomalous level repulsion in the absence of time-reversal symmetry.Comment: 10 pages + 13 fig

Dual inhibition of CDK12 and CDK13 uncovers actionable vulnerabilities in patient-derived ovarian cancer organoids

Background: High grade serous ovarian cancer (HGSOC) is highly lethal, partly due to chemotherapy resistance and limited availability of targeted approaches. Cyclin dependent kinases 12 and 13 (CDK12/13) are promising therapeutic targets in human cancers, including HGSOC. Nevertheless, the effects of their inhibition in HGSOC and the potential synergy with other drugs are poorly known. Methods: We analyzed the effects of the CDK12/13 inhibitor THZ531 in HGSOC cells and patient-derived organoids (PDOs). RNA sequencing and quantitative PCR analyses were performed to identify the genome-wide effects of short-term CDK12/13 inhibition on the transcriptome of HGSOC cells. Viability assays with HGSOC cells and PDOs were performed to assess the efficacy of THZ531 as single agent or in combination with clinically relevant drugs. Results: The CDK12 and CDK13 genes are deregulated in HGSOC and their concomitant up-regulation with the oncogene MYC predicts poor prognosis. HGSOC cells and PDOs display high sensitivity to CDK12/13 inhibition, which synergizes with drugs in clinical use for HGSOC. Transcriptome analyses revealed cancer-relevant genes whose expression is repressed by dual CDK12/13 inhibition through impaired splicing. Combined treatment with THZ531 and inhibitors of pathways regulated by these cancer relevant genes (EGFR, RPTOR, ATRIP) exerted synergic effects on HGSOC PDO viability. Conclusions: CDK12 and CDK13 represent valuable therapeutic targets for HGSOC. We uncovered a wide spectrum of CDK12/13 targets as potential therapeutic vulnerabilities for HGSOC. Moreover, our study indicates that CDK12/13 inhibition enhances the efficacy of approved drugs that are already in use for HGSOC or other human cancers