Flexible and expandable robot for tissue therapies - Modeling and design

Objective: Implantable technologies should be mechanically compliant with the tissue in order to maximize tissue quality and reduce inflammation during tissue reconstruction. We introduce the development of a flexible and expandable implantable robotic (FEIR) device for the regenerative elongation of tubular tissue by applying controlled and precise tension to the target tissue while minimizing the forces produced on the surrounding tissue. Methods: We introduce a theoretical framework based on iterative beam theory static analysis for the design of an expandable robot with a flexible rack. The model takes into account the geometry and mechanics of the rack to determine a trade-off between its stiffness and capability to deliver the required tissue tension force. We empirically validate this theory on the benchtop and with biological tissue. Results: We show that FEIR can apply the required therapeutical forces on the tissue while reducing the amount of force it applies to the surrounding tissues as well as reducing self-damage. Conclusion: The study demonstrates a method to develop robots that can change size and shape to fit their dynamic environment while maintaining the precision and delicacy necessary to manipulate tissue by traction. Significance: The method is relevant to designers of implantable technologies. The robot is a precursor medical device for the treatment of Long-Gap Esophageal Atresia and Short Bowel Syndrome

Improving genome assemblies using multi-platform sequence data

Accurate de novo assembly using short reads generated by next generation sequencing technologies is still an open problem. Although there are several assembly algorithms developed for data generated with different sequencing technologies, and some that can make use of hybrid data, the assemblies are still far from being perfect. There is still a need for computational approaches to improve draft assemblies. Here we propose a new method to correct assembly mistakes when there are multiple types of data generated using different sequencing technologies that have different strengths and biases. We exploit the assembly of highly accurate short reads to correct the contigs obtained from less accurate long reads. We apply our method to Illumina, 454, and Ion Torrent data, and also compare our results with existing hybrid assemblers, Celera and Masurca. © Springer International Publishing Switzerland 2016

Probing ISM Structure in Trumpler 14 & Carina I Using The Stratospheric Terahertz Observatory 2

We present observations of the Trumpler 14/Carina I region carried out using the Stratospheric Terahertz Observatory 2 (STO2). The Trumpler 14/Carina I region is in the west part of the Carina Nebula Complex, which is one of the most extreme star-forming regions in the Milky Way. We observed Trumpler 14/Carina I in the 158 $\mu$m transition of [C\,{\sc ii}] with a spatial resolution of 48$''$ and a velocity resolution of 0.17 km s$^{-1}$. The observations cover a 0.25$^\circ$ by 0.28$^\circ$ area with central position {\it l} = 297.34$^\circ$, {\it b} = -0.60$^\circ$. The kinematics show that bright [C\,{\sc ii}] structures are spatially and spectrally correlated with the surfaces of CO clouds, tracing the photodissociation region and ionization front of each molecular cloud. Along 7 lines of sight that traverse Tr 14 into the dark ridge to the southwest, we find that the [C\,{\sc ii}] luminosity from the HII region is 3.7 times that from the PDR. In same los we find in the PDRs an average ratio of 1:4.1:5.6 for the mass in atomic gas:dark-CO gas: molecular gas traced by CO. Comparing multiple gas tracers including HI 21cm, [C\,{\sc ii}], CO, and radio recombination lines, we find that the HII regions of the Carina Nebula Complex are well-described as HII regions with one-side freely expanding towards us, consistent with the champagne model of ionized gas evolution. The dispersal of the GMC in this region is dominated by EUV photoevaporation; the dispersal timescale is 20-30 Myr.Comment: ApJ accepte

Record linkage to obtain birth outcomes for the evaluation of screening biomarkers in pregnancy: a feasibility study

<p>Abstract</p> <p>Background</p> <p>Linking population health data to pathology data is a new approach for the evaluation of predictive tests that is potentially more efficient, feasible and efficacious than current methods. Studies evaluating the use of first trimester maternal serum levels as predictors of complications in pregnancy have mostly relied on resource intensive methods such as prospective data collection or retrospective chart review. The aim of this pilot study is to demonstrate that record-linkage between a pathology database and routinely collected population health data sets provides follow-up on patient outcomes that is as effective as more traditional and resource-intensive methods. As a specific example, we evaluate maternal serum levels of PAPP-A and free <it>β</it>-hCG as predictors of adverse pregnancy outcomes, and compare our results with those of prospective studies.</p> <p>Methods</p> <p>Maternal serum levels of PAPP-A and free <it>β</it>-hCG for 1882 women randomly selected from a pathology database in New South Wales (NSW) were linked to routinely collected birth and hospital databases. Crude relative risks were calculated to investigate the association between low levels (multiples of the median ≤ 5^thpercentile) of PAPP-A or free <it>β</it>-hCG and the outcomes of preterm delivery (<37 weeks), small for gestational age (<10^thpercentile), fetal loss and stillbirth.</p> <p>Results</p> <p>Using only full name, sex and date of birth for record linkage, pregnancy outcomes were available for 1681 (89.3%) of women included in the study. Low levels of PAPP-A had a stronger association with adverse pregnancy outcomes than a low level of free <it>β</it>-hCG which is consistent with results in published studies. The relative risk of having a preterm birth with a low maternal serum PAPP-A level was 3.44 (95% CI 1.96–6.10) and a low free <it>β</it>-hCG level was 1.31 (95% CI 0.55–6.16).</p> <p>Conclusion</p> <p>This study provides data to support the use of record linkage for outcome ascertainment in studies evaluating predictive tests. Linkage proportions are likely to increase if more personal identifiers are available. This method of follow-up is a cost-efficient technique and can now be applied to a larger cohort of women.</p

Bias associated with delayed verification in test accuracy studies: accuracy of tests for endometrial hyperplasia may be much higher than we think!

BACKGROUND: To empirically evaluate bias in estimation of accuracy associated with delay in verification of diagnosis among studies evaluating tests for predicting endometrial hyperplasia. METHODS: Systematic reviews of all published research on accuracy of miniature endometrial biopsy and endometr ial ultrasonography for diagnosing endometrial hyperplasia identified 27 test accuracy studies (2,982 subjects). Of these, 16 had immediate histological verification of diagnosis while 11 had verification delayed > 24 hrs after testing. The effect of delay in verification of diagnosis on estimates of accuracy was evaluated using meta-regression with diagnostic odds ratio (dOR) as the accuracy measure. This analysis was adjusted for study quality and type of test (miniature endometrial biopsy or endometrial ultrasound). RESULTS: Compared to studies with immediate verification of diagnosis (dOR 67.2, 95% CI 21.7–208.8), those with delayed verification (dOR 16.2, 95% CI 8.6–30.5) underestimated the diagnostic accuracy by 74% (95% CI 7%–99%; P value = 0.048). CONCLUSION: Among studies of miniature endometrial biopsy and endometrial ultrasound, diagnostic accuracy is considerably underestimated if there is a delay in histological verification of diagnosis

Identification of a gene signature for discriminating metastatic from primary melanoma using a molecular interaction network approach

Understanding the biological factors that are characteristic of metastasis in melanoma remains a key approach to improving treatment. In this study, we seek to identify a gene signature of metastatic melanoma. We configured a new network-based computational pipeline, combined with a machine learning method, to mine publicly available transcriptomic data from melanoma patient samples. Our method is unbiased and scans a genome-wide protein-protein interaction network using a novel formulation for network scoring. Using this, we identify the most influential, differentially expressed nodes in metastatic as compared to primary melanoma. We evaluated the shortlisted genes by a machine learning method to rank them by their discriminatory capacities. From this, we identified a panel of 6 genes, ALDH1A1, HSP90AB1, KIT, KRT16, SPRR3 and TMEM45B whose expression values discriminated metastatic from primary melanoma (87% classification accuracy). In an independent transcriptomic data set derived from 703 primary melanomas, we showed that all six genes were significant in predicting melanoma specific survival (MSS) in a univariate analysis, which was also consistent with AJCC staging. Further, 3 of these genes, HSP90AB1, SPRR3 and KRT16 remained significant predictors of MSS in a joint analysis (HR = 2.3, P = 0.03) although, HSP90AB1 (HR = 1.9, P = 2 × 10−4) alone remained predictive after adjusting for clinical predictors

Meta-Profiles of Gene Expression during Aging: Limited Similarities between Mouse and Human and an Unexpectedly Decreased Inflammatory Signature

Background: Skin aging is associated with intrinsic processes that compromise the structure of the extracellular matrix while promoting loss of functional and regenerative capacity. These processes are accompanied by a large-scale shift in gene expression, but underlying mechanisms are not understood and conservation of these mechanisms between humans and mice is uncertain. Results: We used genome-wide expression profiling to investigate the aging skin transcriptome. In humans, age-related shifts in gene expression were sex-specific. In females, aging increased expression of transcripts associated with T-cells, B-cells and dendritic cells, and decreased expression of genes in regions with elevated Zeb1, AP-2 and YY1 motif density. In males, however, these effects were contrasting or absent. When age-associated gene expression patterns in human skin were compared to those in tail skin from CB6F1 mice, overall human-mouse correspondence was weak. Moreover, inflammatory gene expression patterns were not induced with aging of mouse tail skin, and well-known aging biomarkers were in fact decreased (e.g., Clec7a, Lyz1 and Lyz2). These unexpected patterns and weak human-mouse correspondence may be due to decreased abundance of antigen presenting cells in mouse tail skin with age. Conclusions: Aging is generally associated with a pro-inflammatory state, but we have identified an exception to this pattern with aging of CB6F1 mouse tail skin. Aging therefore does not uniformly heighten inflammatory status across all mouse tissues. Furthermore, we identified both intercellular and intracellular mechanisms of transcriptome aging, including those that are sex- and species-specific

Connecting the data landscape of long-term ecological studies: The SPI-Birds data hub

The integration and synthesis of the data in different areas of science is drastically slowed and hindered by a lack of standards and networking programmes. Long-term studies of individually marked animals are not an exception. These studies are especially important as instrumental for understanding evolutionary and ecological processes in the wild. Furthermore, their number and global distribution provides a unique opportunity to assess the generality of patterns and to address broad-scale global issues (e.g. climate change). To solve data integration issues and enable a new scale of ecological and evolutionary research based on long-term studies of birds, we have created the SPI-Birds Network and Database (www.spibirds.org)\u2014a large-scale initiative that connects data from, and researchers working on, studies of wild populations of individually recognizable (usually ringed) birds. Within year and a half since the establishment, SPI-Birds has recruited over 120 members, and currently hosts data on almost 1.5 million individual birds collected in 80 populations over 2,000 cumulative years, and counting. SPI-Birds acts as a data hub and a catalogue of studied populations. It prevents data loss, secures easy data finding, use and integration and thus facilitates collaboration and synthesis. We provide community-derived data and meta-data standards and improve data integrity guided by the principles of Findable, Accessible, Interoperable and Reusable (FAIR), and aligned with the existing metadata languages (e.g. ecological meta-data language). The encouraging community involvement stems from SPI-Bird's decentralized approach: research groups retain full control over data use and their way of data management, while SPI-Birds creates tailored pipelines to convert each unique data format into a standard format. We outline the lessons learned, so that other communities (e.g. those working on other taxa) can adapt our successful model. Creating community-specific hubs (such as ours, COMADRE for animal demography, etc.) will aid much-needed large-scale ecological data integration