A competitive cell-permeable peptide impairs Nme-1 (NDPK-A) and Prune-1 interaction: therapeutic applications in cancer.

The understanding of protein–protein interactions is crucial in order to generate a second level of functional genomic analysis in human disease. Within a cellular microenvironment, protein–protein interactions generate new functions that can be defined by single or multiple modes of protein interactions. We outline here the clinical importance of targeting of the Nme-1 (NDPK-A)–Prune-1 protein complex in cancer, where an imbalance in the formation of this protein–protein complex can result in inhibition of tumor progression. We discuss here recent functional data using a small synthetic competitive cell-permeable peptide (CPP) that has shown therapeutic efficacy for impairing formation of the Nme-1–Prune-1 protein complex in mouse preclinical xenograft tumor models (e.g., breast, prostate, colon, and neuroblastoma). We thus believe that further discoveries in the near future related to the identification of new protein–protein interactions will have great impact on the development of new therapeutic strategies against various cancers

Leveraging Kernelized Synergies on Shared Subspace for Precision Grasping and Dexterous Manipulation

Manipulation in contrast to grasping is a trajectorial task that needs to use dexterous hands. Improving the dexterity of robot hands, increases the controller complexity and thus requires to use the concept of postural synergies. Inspired from postural synergies, this research proposes a new framework called kernelized synergies that focuses on the re-usability of same subspace for precision grasping and dexterous manipulation. In this work, the computed subspace of postural synergies is parameterized by kernelized movement primitives to preserve its grasping and manipulation characteristics and allows its reuse for new objects. The grasp stability of proposed framework is assessed with the force closure quality index, as a cost function. For performance evaluation, the proposed framework is initially tested on two different simulated robot hand models using the Syngrasp toolbox and experimentally, four complex grasping and manipulation tasks are performed and reported. Results confirm the hand agnostic approach of proposed framework and its generalization to distinct objects irrespective of their dimensions

Experimental evaluation of synergy-based in-hand manipulation

In this paper, the problem of in-hand dexterous manipulation has been addressed on the base of postural synergies analysis. The computation of the synergies subspace able to represent grasp and manipulation tasks as trajectories connecting suitable configuration sets is based on the observation of the human hand behavior. Five subjects are required to reproduce themost natural grasping configuration belonging to the considered grasping taxonomy and the boundary configurations for those grasps that admit internal manipulation. The measurements on the human hand and the reconstruction of the human grasp configurations are obtained using a vision-based mapping method that assume the kinematics of the robotic hand, used for the experiments, as a simplified model of the human hand. The analysis to determine the most suitable set of synergies able to reproduce the selected grasps and the relative allowed internal manipulation has been carried out. The grasping and in-hand manipulation tasks have been reproduced bymeans of linear interpolation of the boundary configurations in the selected synergies subspace and the results have been experimentally tested on the UB Hand IV

Influence of laser-lok surface on immediate functional loading of implants in single-tooth replacement: a 2-year prospective clinical study.

he purpose of this study was to evaluate the influence of a Laser-Lok microtexturing surface on clinical attachment level and crestal bone remodeling around immediately functionally loaded implants in single-tooth replacement. Seventy-seven patients were included in a prospective, randomized study and divided into two groups. Group 1 (control) consisted of non-Laser-Lok type implants (n = 39), while in group 2 (test), Laser-Lok type implants were used (n = 39). Crestal bone loss (CBL) and clinical parameters including clinical attachment level (CAL), Plaque Index (PI), and bleeding on probing were recorded at baseline examinations and at 6, 12, and 24 months after loading with the final restoration. One implant was lost in the control group and one in the test group, giving a total survival rate of 96.1% after 2 years. PI and BOP outcomes were similar for both implant types without statistical differences. A mean CAL loss of 1.10 ± 0.51 mm was observed during the first 2 years in group 1, while the mean CAL loss observed in group 2 was 0.56 ± 0.33 mm. Radiographically, group 1 implants showed a mean crestal bone loss of 1.07 ± 0.30 mm compared with 0.49 ± 0.34 mm for group 2. The type of implant did not influence the survival rate, whereas Laser-Lok implants resulted in greater CAL and in shallower radiographic peri-implant CBL than non-Laser-Lok implants

The PRISMA Hand II: A Sensorized Robust Hand for Adaptive Grasp and In-Hand Manipulation

Although substantial progresses have been made in building anthropomorphic robotic hands, lack of mechanical robustness, dexterity and force sensation still restrains wide adoption of robotic prostheses. This paper presents the design and preliminary evaluation of the PRISMA hand II, which is a mechanically robust anthropomorphic hand developed at the PRISMA Lab of University of Naples Federico II. The hand is highly underactuated, as the 19 finger joints are driven by three motors via elastic tendons. Nevertheless, the hand can performs not only adaptive grasps but also in-hand manipulation. The hand uses rolling contact joints, which is compliant in multiple directions. Force sensor are integrated to each fingertip in order to provide force feedback during grasping and manipulation. Preliminary experiments have been performed to evaluate the hand. Results show that the hand can perform various grasps and in-hand manipulation, while the structure can withstand severe disarticulation. This suggests that the proposed design can be a viable solution for robust and dexterous prosthetic hands

Forecasting SYM-H Index: A Comparison Between LongShort-Term Memory and Convolutional Neural Networks

Forecasting geomagnetic indices represents a key point to develop warning systems for the mitigation of possible effects of severe geomagnetic storms on critical ground infrastructures. Here we focus on SYM‐H index, a proxy of the axially symmetric magnetic field disturbance at low and middle latitudes on the Earth's surface. To forecast SYM‐H, we built two artificial neural network (ANN) models and trained both of them on two different sets of input parameters including interplanetary magnetic field components and magnitude and differing for the presence or not of previous SYM‐H values. These ANN models differ in architecture being based on two conceptually different neural networks: the long short‐term memory (LSTM) and the convolutional neural network (CNN). Both networks are trained, validated, and tested on a total of 42 geomagnetic storms among the most intense that occurred between 1998 and 2018. Performance comparison of the two ANN models shows that (1) both are able to well forecast SYM‐H index 1 h in advance, with an accuracy of more than 95% in terms of the coefficient of determination R2; (2) the model based on LSTM is slightly more accurate than that based on CNN when including SYM‐H index at previous steps among the inputs; and (3) the model based on CNN has interesting potentialities being more accurate than that based on LSTM when not including SYM‐H index among the inputs. Predictions made including SYM‐H index among the inputs provide a root mean squared error on average 42% lower than that of predictions made without SYM‐H

ORBIT CODES FROM FORMS ON VECTOR SPACES OVER A FINITE FIELD

In this paper we construct different families of orbit codes in the vector spaces of the symmetric bilinear forms, quadratic forms and Hermitian forms on an n-dimensional vector space over the finite field Fq. All these codes admit the general linear group GL(n, q) as a transitive automorphism group