Metallopanstimulin as a marker for head and neck cancer

BACKGROUND: Metallopanstimulin (MPS-1) is a ribosomal protein that is found in elevated amounts in the sera of patients with head and neck squamous cell carcinoma (HNSCC). We used a test, denoted MPS-H, which detects MPS-1 and MPS-1-like proteins, to determine the relationship between MPS-H serum levels and clinical status of patients with, or at risk for, HNSCC. PATIENTS AND METHODS: A total of 125 patients were prospectively enrolled from a university head and neck oncology clinic. Participants included only newly diagnosed HNSCC patients. Two control groups, including 25 non-smokers and 64 smokers, were studied for comparison. A total of 821 serum samples collected over a twenty-four month period were analyzed by the MPS-H radioimmunoassay. RESULTS: HNSCC, non-smokers, and smokers had average MPS-H values of 41.5 ng/mL, 10.2 ng/mL, and 12.8 ng/mL, respectively (p = 0.0001). CONCLUSION: We conclude that MPS-1 and MPS-1-like proteins are elevated in patients with HNSCC, and that MPS-H appears to be a promising marker of presence of disease and response to treatment in HNSCC patients

Geographical Hot Spot Analysis of ATAPS for Policy Planning

Studies on equity of mental health referrals have used qualitative approaches or service utilisation data, however little information is available on spatial equity. The Access to Allied Psychological Services (ATAPS) program enables patients to be referred to mental health professionals for lowcost mental health care to facilitate equality of care

Bibliometric Analysis of Psychomotricity Research Trends: The Current Role of Childhood

Psychomotricity is a wide broad term, which encompasses different bodily action approaches to support children and adolescents to achieve their highest potential. A search on the Web of Science (WoS) Core Collection database was performed on this topic, using traditional bibliometric laws. Finally, 118 publications (112 articles and 6 reviews) documents were found. Annual publications presented an exponentially growing trend (R2 = 84.7%). Spain was the most productive country/region worldwide. Paola Magioncalda, Matteo Martino y Víctor Arufe Giraldez were highlighted as the most prolific co-authors. “Retos Nuevas Tendencias en Educación Física, Deporte y Recreación” was the most productive journal and the “International Journal of Environmental Research and Public Health”, was the second most productive; the third in the list was the most productive in the JCR ranking. Thus, research on psychomotricity is experiencing exponential growth, causing this topic to generate great interest among researchers, publishers and journals. The most cited paper was “Neurocognitive Effects of Alcohol Hangover”. The author keywords that were first raised together with psychomotricity were related to rehabilitation and psychomotor development, while the current trend was focused on physical activity and early childhood education

Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking

Discriminative Correlation Filters (DCF) have demonstrated excellent performance for visual object tracking. The key to their success is the ability to efficiently exploit available negative data by including all shifted versions of a training sample. However, the underlying DCF formulation is restricted to single-resolution feature maps, significantly limiting its potential. In this paper, we go beyond the conventional DCF framework and introduce a novel formulation for training continuous convolution filters. We employ an implicit interpolation model to pose the learning problem in the continuous spatial domain. Our proposed formulation enables efficient integration of multi-resolution deep feature maps, leading to superior results on three object tracking benchmarks: OTB-2015 (+5.1% in mean OP), Temple-Color (+4.6% in mean OP), and VOT2015 (20% relative reduction in failure rate). Additionally, our approach is capable of sub-pixel localization, crucial for the task of accurate feature point tracking. We also demonstrate the effectiveness of our learning formulation in extensive feature point tracking experiments. Code and supplementary material are available at http://www.cvl.isy.liu.se/research/objrec/visualtracking/conttrack/index.html.Comment: Accepted at ECCV 201

Tunable uptake of poly(ethylene oxide) by graphite-oxide-based materials

We investigate the role of structure and chemical composition on the uptake of poly(ethylene oxide) by a series of graphite oxides (GOs) and thermally reduced GOs, leading to the formation of polymer-intercalated GO and polymer-adsorbed graphene nanostructures. To this end, a series of poly(ethylene oxide) (PEO) - GO hybrid materials exhibiting a variable degree of GO oxidation and exfoliation has been investigated in detail using a combination of techniques including X-ray photoelectron spectroscopy, X-ray diffraction, thermogravimetry, scanning-electron microscopy, and nitrogen adsorption. Intercalation of the polymer phase into well-defined GO galleries is found to correlate well with both the degree of GO oxidation and with the presence of hydroxyl groups. The latter feature is an essential prerequisite to optimize polymer uptake owing to the predominance of hydrogen-bonding interactions between intercalant and host. Unlike the bulk polymer, these intercalation compounds show neither crystallisation nor glass-transition associated with the polymer phase. Exfoliation and reduction of GO result in high-surface-area graphene layers exhibiting the highest polymer uptake in these GO-based materials. In this case, PEO undergoes surface adsorption, where we observe the recovery of glass and melting transitions associated with the polymer phase albeit at significantly lower temperatures than the bulk

A Methodology for Detecting Field Potentials from the External Ear Canal: NEER and EVestG

An algorithm called the neural event extraction routine (NEER) and a method called Electrovestibulography (EVestG) for extracting field potentials (FPs) from artefact rich and noisy ear canal recordings is presented. Averaged FP waveforms can be used to aid detection of acoustic and or vestibular pathologies. FPs were recorded in the external ear canal proximal to the ear drum. These FPs were extracted using an algorithm called NEER. NEER utilises a modified complex Morlet wavelet analysis of phase change across multiple scales and a template matching (matched filter) methodology to detect FPs buried in noise and biological and environmental artefacts. Initial simulation with simulated FPs shows NEER detects FPs down to −30 dB SNR (power) but only 13–23% of those at SNR’s <−6 dB. This was deemed applicable to longer duration recordings wherein averaging could be applied as many FPs are present. NEER was applied to detect both spontaneous and whole body tilt evoked FPs. By subtracting the averaged tilt FP response from the averaged spontaneous FP response it is believed this difference is more representative of the vestibular response. Significant difference (p < 0.05) between up and down whole body (supine and sitting) movements was achieved. Pathologic and physiologic evidence in support of a vestibular and acoustic origin is also presented

Novel efficient genome-wide SNP panels for the conservation of the highly endangered Iberian lynx

Background: The Iberian lynx (Lynx pardinus) has been acknowledged as the most endangered felid species in the world. An intense contraction and fragmentation during the twentieth century left less than 100 individuals split in two isolated and genetically eroded populations by 2002. Genetic monitoring and management so far have been based on 36 STRs, but their limited variability and the more complex situation of current populations demand more efficient molecular markers. The recent characterization of the Iberian lynx genome identified more than 1.6 million SNPs, of which 1536 were selected and genotyped in an extended Iberian lynx sample. Methods: We validated 1492 SNPs and analysed their heterozygosity, Hardy-Weinberg equilibrium, and linkage disequilibrium. We then selected a panel of 343 minimally linked autosomal SNPs from which we extracted subsets optimized for four different typical tasks in conservation applications: individual identification, parentage assignment, relatedness estimation, and admixture classification, and compared their power to currently used STR panels. Results: We ascribed 21 SNPs to chromosome X based on their segregation patterns, and identified one additional marker that showed significant differentiation between sexes. For all applications considered, panels of autosomal SNPs showed higher power than the currently used STR set with only a very modest increase in the number of markers. Conclusions: These novel panels of highly informative genome-wide SNPs provide more powerful, efficient, and flexible tools for the genetic management and non-invasive monitoring of Iberian lynx populations. This example highlights an important outcome of whole-genome studies in genetically threatened species

Voxel-Based Solution Approaches to the Three-Dimensional Irregular Packing Problem

Research on the three-dimensional (3D) packing problem has largely focused on packing boxes for the transportation of goods. As a result, there has been little focus on packing irregular shapes in the operational research literature. New technologies have raised the practical importance of 3D irregular packing problems and the need for efficient solutions. In this work, we address the variant of the problem where the aim is to place a set of 3D irregular items in a container, while minimizing the container height, analogous to the strip packing problem. In order to solve this problem, we need to address two critical components; efficient computation of the geometry and finding high-quality solutions. In this work, we explore the potential of voxels, the 3D equivalent of pixels, as the geometric representation of the irregular items. In this discretised space, we develop a geometric tool that extends the concept of the nofit polygon to the 3D case. This enables us to provide an integer linear programming formulation for this problem that can solve some small instances. For practical size problems, we design metaheuristic optimisation approaches. Because the literature is limited, we introduce new benchmark instances. Some are randomly generated and some represent realistic models from the additive manufacturing area. Our results on the literature benchmark data and on our new instances show that our metaheuristic techniques achieve the best known solutions for a wide variety of problems in practical computation times