Five-year publication rate of clinical presentations at the open and closed American shoulder and elbow surgeons annual meeting from 2005–2010

© 2016, The Author(s). Background: The purpose of this study was to evaluate the five-year publication rate of papers presented at both the open and closed American Shoulder and Elbow Surgeons’ (ASES) annual meetings from 2005 to 2010. Methods: Online abstracts of the presentations at the open and closed ASES annual meetings were independently screened for clinical studies and graded for quality using level of evidence. The databases PubMed (MEDLINE), Ovid (MEDLINE), and EMBASE were comprehensively searched for full-text publications corresponding to these presentations and any paper published within five years of the presentation date was counted. Results: Overall, 131/266 papers corresponding to the meeting presentations were identified for a five-year publication rate of 49.2 %. Sixty two (48 %) of the papers were published in The Journal of Shoulder and Elbow Surgeons, 23 (18 %) were published in The American Journal of Sports Medicine, and 20 (16 %) were published in The Journal of Bone and Joint Surgery. The mean patient sample size included in presentations with a subsequent full-text publication was higher (154; standard error =27) than the presentations not published (93; standard error = 13) (p = 0.039). There was no correlation (p = 0.248) between the publication rate and the level of evidence of the presentations. Conclusions: The publication rate of presentations at ASES meetings from 2005 to 2010 is similar to that reported from other orthopaedic meetings. Studies with large sample sizes should continue to be encouraged, and high quality presentations must consistently be followed up with full-text manuscript preparation in order to maximize the future clinical impact

An Efficient Block Circulant Preconditioner For Simulating Fracture Using Large Fuse Networks

{\it Critical slowing down} associated with the iterative solvers close to the critical point often hinders large-scale numerical simulation of fracture using discrete lattice networks. This paper presents a block circlant preconditioner for iterative solvers for the simulation of progressive fracture in disordered, quasi-brittle materials using large discrete lattice networks. The average computational cost of the present alorithm per iteration is $O(rs log s) + delops$, where the stiffness matrix ${\bf A}$ is partioned into $r$-by-$r$ blocks such that each block is an $s$-by-$s$ matrix, and $delops$ represents the operational count associated with solving a block-diagonal matrix with $r$-by-$r$ dense matrix blocks. This algorithm using the block circulant preconditioner is faster than the Fourier accelerated preconditioned conjugate gradient (PCG) algorithm, and alleviates the {\it critical slowing down} that is especially severe close to the critical point. Numerical results using random resistor networks substantiate the efficiency of the present algorithm.Comment: 16 pages including 2 figure

Crashworthiness simulation of composite automotive structures

In 1990 the Automotive Composites Consortium (ACC) began the investigation of crash worthiness simulation methods for composite materials. A contract was given to Livermore Software Technology Corporation (LSTC) to implement a new damage model in LS-DYNA3DTM specifically for composite structures. This model is in LS-DYNA3DTM and is in use by the ACC partners. In 1994 USCAR, a partnership of American auto companies, entered into a partnership called SCAAP (Super Computing Automotive Applications Partnership) for the express purpose of working with the National Labs on computational oriented research. A CRADA (Cooperative Research and Development Agreement) was signed with Lawrence Livermore National Laboratory, Oak Ridge National Laboratory, Sandia National Laboratory, Argonne National Laboratory, and Los Alamos National Laboratory to work in three distinctly different technical areas, one of which was composites material modeling for crash worthiness. Each Laboratory was assigned a specific modeling task. The ACC was responsible for the technical direction of the composites project and provided all test data for code verification. All new models were to be implemented in DYNA3D and periodically distributed to all partners for testing. Several new models have been developed and implemented. Excellent agreement has been shown between tube crush simulation and experiments

Liposome Co-sedimentation and Co-flotation Assays to Study Lipid-Protein Interactions

A large proportion of proteins are expected to interact with cellular membranes to carry out their physiological functions in processes such as membrane transport, morphogenesis, cytoskeletal organization, and signal transduction. The recruitment of proteins at the membrane-cytoplasm interface and their activities are precisely regulated by phosphoinositides, which are negatively charged phospholipids found on the cytoplasmic leaflet of cellular membranes and play critical roles in membrane homeostasis and cellular signaling. Thus, it is important to reveal which proteins interact with phosphoinositides and to elucidate the underlying mechanisms. Here, we present two standard in vitro methods, liposome co-sedimentation and co-flotation assays, to study lipid-protein interactions. Liposomes can mimic various biological membranes in these assays because their lipid compositions and concentrations can be varied. Thus, in addition to mechanisms of lipid-protein interactions, these methods provide information on the possible specificities of proteins toward certain lipids such as specific phosphoinositide species and can hence shed light on the roles of membrane interactions on the functions of membrane-associated proteins.Peer reviewe

Glaucoma diagnosis using multi-feature analysis and a deep learning technique

AbstractIn this study, we aimed to facilitate the current diagnostic assessment of glaucoma by analyzing multiple features and introducing a new cross-sectional optic nerve head (ONH) feature from optical coherence tomography (OCT) images. The data (n = 100 for both glaucoma and control) were collected based on structural, functional, demographic and risk factors. The features were statistically analyzed, and the most significant four features were used to train machine learning (ML) algorithms. Two ML algorithms: deep learning (DL) and logistic regression (LR) were compared in terms of the classification accuracy for automated glaucoma detection. The performance of the ML models was evaluated on unseen test data, n = 55. An image segmentation pilot study was then performed on cross-sectional OCT scans. The ONH cup area was extracted, analyzed, and a new DL model was trained for glaucoma prediction. The DL model was estimated using five-fold cross-validation and compared with two pre-trained models. The DL model trained from the optimal features achieved significantly higher diagnostic performance (area under the receiver operating characteristic curve (AUC) 0.98 and accuracy of 97% on validation data and 96% on test data) compared to previous studies for automated glaucoma detection. The second DL model used in the pilot study also showed promising outcomes (AUC 0.99 and accuracy of 98.6%) to detect glaucoma compared to two pre-trained models. In combination, the result of the two studies strongly suggests the four features and the cross-sectional ONH cup area trained using deep learning have a great potential for use as an initial screening tool for glaucoma which will assist clinicians in making a precise decision.</jats:p

Morphology of two dimensional fracture surface

We consider the morphology of two dimensional cracks observed in experimental results obtained from paper samples and compare these results with the numerical simulations of the random fuse model (RFM). We demonstrate that the data obey multiscaling at small scales but cross over to self-affine scaling at larger scales. Next, we show that the roughness exponent of the random fuse model is recovered by a simpler model that produces a connected crack, while a directed crack yields a different result, close to a random walk. We discuss the multiscaling behavior of all these models.Comment: slightly revise

Do EnChroma glasses improve color vision for colorblind subjects?

The commercialization of EnChroma glasses has generated great expectations for people to be able to see new colors or even correct color vision deficiency (CVD). We evaluate the effectiveness of these glasses using two complementary strategies for the first time. The first consists of using the three classical types of tests — recognition, arrangement and discrimination — with and without glasses, with a high number of individuals. In the second, we use the spectral transmittance of the glasses to simulate the appearance of stimuli in a set of scenes for normal observers and observers with CVD. The results show that the glasses introduce a variation of the perceived color, but neither improve results in the diagnosis tests nor allow the observers with CVD to have a more normal color vision.Spanish State Agency of Research (AEI); Ministry for Economy, Industry and Competitiveness (MIMECO) (Grant numbers FIS2017-89258-P and DPI 2015-64571-R); European Union FEDER (European Regional Development Funds)

Widespread sex differences in gene expression and splicing in the adult human brain

There is strong evidence to show that men and women differ in terms of neurodevelopment, neurochemistry and susceptibility to neurodegenerative and neuropsychiatric disease. The molecular basis of these differences remains unclear. Progress in this field has been hampered by the lack of genome-wide information on sex differences in gene expression and in particular splicing in the human brain. Here we address this issue by using post-mortem adult human brain and spinal cord samples originating from 137 neuropathologically confirmed control individuals to study whole-genome gene expression and splicing in 12 CNS regions. We show that sex differences in gene expression and splicing are widespread in adult human brain, being detectable in all major brain regions and involving 2.5% of all expressed genes. We give examples of genes where sex-biased expression is both disease-relevant and likely to have functional consequences, and provide evidence suggesting that sex biases in expression may reflect sex-biased gene regulatory structures