bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tissue-specific genes as an underutilized resource in drug discovery
Authors: Ryaboshapkina Maria , Hammar Mårten 
Published: May 2019

AbstractTissue-specific genes are believed to be good drug targets due to improved safety. Here we show that this intuitive notion is not reflected in phase 1 and 2 clinical trials, despite the historic success of tissue-specific targets and their 2.3-fold overrepresentation among targets of marketed non-oncology drugs. We compare properties of tissue-specific genes and drug targets. We show that tissue-specificity of the target may also be related to efficacy of the drug. The relationship may be indirect (enrichment in Mendelian disease and PTVesc genes) or direct (elevated betweenness centrality scores for tissue-specifically produced enzymes and secreted proteins). Reduced evolutionary conservation of tissue-specific genes may represent a bottleneck for drug projects, prompting development of novel models with smaller evolutionary gap to humans. We show that the opportunities to identify tissue-specific drug targets are not exhausted and discuss potential use cases for tissue-specific genes in drug research.
FEZF1-AS1 functions as an oncogenic lncRNA in retinoblastoma
Authors: Quan Lian-Jiao , Wang Wen-Jun 
Published: May 2019

Abstract
Long non-coding RNA (lncRNA) FEZF1 antisense RNA 1 (FEZF1-AS1) has been shown to be up-regulated in tumor tissues and cells, and exerts oncogenic effects on various types of malignancies. However, the expression and function of FEZF1-AS1 was still fully unclear in retinoblastoma. The purpose of our study was to investigate the expression and clinical value of FEZF1-AS1 in retinoblastoma patients, and explore the effect of FEZF1-AS1 on retinoblastoma cell proliferation, migration and invasion. In our results, levels of FEZF1-AS1 expression were elevated in retinoblastoma tissue specimens and cell lines compared with adjacent normal retina tissue specimens and human retinal pigment epithelial cell line, respectively. The correlation analysis indicated that high FEZF1-AS1 expression was significantly correlated with present choroidal invasion and optic nerve invasion. Survival analysis suggested that retinoblastoma patients in high FEZF1-AS1 expression group had obviously short disease-free survival (DFS) compared with retinoblastoma patients in low FEZF1-AS1 expression group, and high FEZF1-AS1 expression was an independent unfavorable prognostic factor for DFS in retinoblastoma patients. Loss-of-function study indicated silencing FEZF1-AS1 expression inhibited retinoblastoma cell proliferation, invasion and migration. In conclusion, FEZF1-AS1 functions as an oncogenic lncRNA in retinoblastoma.
Reconstruction Techniques in IceCube using Convolutional and Generative Neural Networks
Authors: Huennefeld Mirco 
Published: May 2019

Reliable and accurate reconstruction methods are vital to the success of high-energy physics experiments such as IceCube. Machine learning based techniques, in particular deep neural networks, can provide a viable alternative to maximum-likelihood methods. However, most common neural network architectures were developed for other domains such as image recogntion. While these methods can enhance the reconstruction performance in IceCube, there is much potential for tailored techniques. In the typical physics use-case, many symmetries, invariances and prior knowledge exist in the data, which are not fully exploited by current network architectures. Novel and specialized deep learning based reconstruction techniques are desired which can leverage the physics potential of experiments like IceCube.
A reconstruction method using convolutional neural networks is presented which can significantly increase the reconstruction accuracy while greatly reducing the runtime in comparison to standard reconstruction methods in Ice- Cube. In addition, first results are discussed for future developments based on generative neural networks.
Preclinical evaluation of peptide-based radiotracers for integrin αvβ6-positive pancreatic carcinoma
Authors: Müller Martin , Altmann Annette , Sauter Max , Lindner Thomas , Jäger Dirk , Rathke Hendrik , Herold-Mende Christel , Marmé Frederik , Babich John , Mier Walter , Haberkorn Uwe 
Published: May 2019

Abstract
Introduction Integrin αvβ6 shows a high expression rate in several cancer entities. As it is absent in most healthy adult tissues, it represents a promising target for tumor targeting with peptidic radiotracers. This study was performed to pave the way of the recently published αvβ6-binding peptide SFLAP3 for the clinical application in patients with pancreatic cancer.
Methods The expression of integrin αvβ6 on several pancreatic cancer cell lines was assessed using flow cytometry and cell binding assays. The affinity was determined in competition binding assays followed by internalization and efflux studies. To increase the affinity, the binding sequence was modified and trimerization of the SFLAP3 peptide was achieved by oxime ligation. PET and biodistribution assays were conducted in Capan-2 tumor bearing mice. Finally, a first pancreatic tumor patient was examined with 68Ga-DOTA-SFLAP3.
Results Flow cytometric analysis and in vitro cell binding revealed high expression of integrin αvβ6 on most pancreatic tumor cell lines. Modification of SFLAP3 led to compounds with improved in vitro binding properties. Unfortunately, these superior properties could not be transferred into improved pharmacokinetics. Consequently, the first pancreatic tumor patient was examined with 68Ga-DOTA-SFLAP3. The PET revealed specific accumulation (with SUV(max) values in the metastases ranging from 5 to 10) and a long retention in the tumor.
Conclusion SFLAP3 showed high affinity to integrin αvβ6 on pancreatic cancer cell lines. The in vitro performance could be confirmed in tumor bearing mice and by PET imaging. These data suggest that DOTA-SFLAP3 is a promising tracer for targeting αvβ6-expressing pancreatic tumors.
A New Percutaneous Endoscopic Instrument for Far-migrated Disk Herniation: A Retrospective Single-Institution Study
Authors: Nakamura Shu , Taguchi Mitsuto 
Published: May 2019

Abstract
Objective Compared with the traditional posterior approach, the transforaminal (TF) approach for percutaneous endoscopic lumbar diskectomy (PELD) in patients with disk herniation has a limited resection range that is problematic to treat far-migrated disk herniation. This study examined the usefulness of a newly developed percutaneous endoscopic instrument for far-migrated disk herniation.
Methods This retrospective study included 22 patients with migrated disk herniation ≥ 10 mm who underwent transforaminal PELD using the new instrument between August 2014 and May 2017. The new instrument differs from conventional forceps because it has only one jaw that rotates in a plane perpendicular to the mouth opening. The migrated herniated disk is held between the instrument and bone surface, pulled out, and subsequently removed using conventional forceps.
Results Herniated disks that had migrated up to 16 mm were removed successfully in all patients.
Conclusions The new instrument is a useful tool that can expand the resection range of the TF approach for PELD.
U-shaped Dural Flap: A Simple Method for Transcranial Skull Base Defect Repair—Technical Report
Authors: Ozdol Cagatay , Aghayev Kamran 
Published: May 2019

AbstractAccidental anterior skull base defects associated with surgery are difficult to treat. There are several methods for the repair, yet postoperative rhinorrhea can occur despite the closure. A 56-year-old female patient was admitted for the treatment of a paraclinoid internal carotid artery aneurysm. The surgery included removal of the anterior clinoid process, unroofing the optic canal, decompressing the optic nerve, and clipping the aneurysm. During the surgery, the planum sphenoidale was accidentally drilled and the nasal cavity exposed. The dural defect was repaired using a U-flap technique. No postoperative cerebrospinal fluid (CSF) rhinorrhea occurred in the patient, and she was discharged on postoperative day 3. On follow-up examination the patient did not have evidence of CSF leakage.
Molecules with dipoles in periodic boundary conditions in a tetragonal cell
Authors: Rutter M J 
Published: May 2019

Abstract
When a system which contains a dipole, and whose dimensionality is less than three, is studied in a code which imposes periodic boundary conditions in all three dimensions, an artificial electric field arises which keeps the potential periodic. This has an impact on the total energy of the system, and on any other attribute which would respond to an electric field. Simple corrections are known for 0D systems embedded in a cubic geometry, and 2D slab systems. This paper shows how the 0D result can be extended to tetragonal geometries, and that for a particular c/a ratio the correction is zero. It also considers an exponential error term absent from the usual consideration of 2D slab geometries, and discusses an empirical form for this.
Optimal parameters for radiation reaction experiments
Authors: Arran C , Cole J M , Gerstmayr E , Blackburn T G , Mangles S P D , Ridgers C P 
Published: May 2019

Abstract
As new laser facilities are developed with intensities on the scale of

10

22

–

10

24

W

cm

−
2

, it becomes ever more important to understand the effect of strong field quantum electrodynamic processes, such as quantum radiation reaction, which will play a dominant role in laser-plasma interactions at these intensities. Recent all-optical experiments, where GeV electrons from a laser wakefield accelerator encountered a counter-propagating laser pulse with a
0 > 10, have produced evidence of radiation reaction, but have not conclusively identified quantum effects nor their most suitable theoretical description. Here we show the number of collisions and the conditions required to accomplish this, based on a simulation campaign of radiation reaction experiments under realistic conditions. We conclude that while the critical energy of the photon spectrum distinguishes classical and quantum-corrected models, a better means of distinguishing the stochastic and deterministic quantum models is the change in the electron energy spread. This is robust against shot-to-shot fluctuations and the necessary laser intensity and electron beam energies are already available. For example, we show that so long as the electron energy spread is below 25%, collisions at a
0 = 10 with electron energies of

500

MeV

could differentiate between different quantum models in under 30 shots, even with shot-to-shot variations at the 50% level.
One large glitch in PSR B1737−30 detected with the TMRT
Authors: Liu Jie , Yan Zhen , Yuan Jian-Ping , Zhao Ru-Shuang , Huang Zhi-Peng , Wu Xin-Ji , Wang Na , Shen Zhi-Qiang 
Published: May 2019

Abstract
One large glitch was detected in PSR B1737–30 using data spanning from MJD 57999 to 58406 obtained with the newly built Shanghai Tian Ma Radio Telescope (TMRT). The glitch took place at the time around MJD 58232.4 when the pulsar underwent an increase in the rotation frequency of Δν about 1.38× 10−6 Hz, corresponding to a fractional step change of Δν/ν ∼ 8.39× 10−7. Post-glitch ν gradually decreased to the pre-glitch value. The frequency derivative was observed to undergo a step change of about −9× 10−16 s−2. Since July 1987, there have been 36 glitches already reported in PSR B1737−30 including this one. According to our analysis, the glitch size distribution is well described by a power law with an index of 1.13. The distribution of the interval between two adjacent glitches (waiting time ΔT) follows a Poisson probability density function. For PSR B1737−30, the interval is prone to be long after a large glitch. However, no correlation is found between glitch size and the interval since the previous glitch.
Enhancing the drug discovery process: Bayesian inference for the analysis and comparison of dose–response experiments
Authors: Labelle Caroline , Marinier Anne , Lemieux Sébastien 
Published: May 2019

Abstract

Motivation
The efficacy of a chemical compound is often tested through dose–response experiments from which efficacy metrics, such as the IC50, can be derived. The Marquardt–Levenberg algorithm (non-linear regression) is commonly used to compute estimations for these metrics. The analysis are however limited and can lead to biased conclusions. The approach does not evaluate the certainty (or uncertainty) of the estimates nor does it allow for the statistical comparison of two datasets. To compensate for these shortcomings, intuition plays an important role in the interpretation of results and the formulations of conclusions. We here propose a Bayesian inference methodology for the analysis and comparison of dose–response experiments.

Results
Our results well demonstrate the informativeness gain of our Bayesian approach in comparison to the commonly used Marquardt–Levenberg algorithm. It is capable to characterize the noise of dataset while inferring probable values distributions for the efficacy metrics. It can also evaluate the difference between the metrics of two datasets and compute the probability that one value is greater than the other. The conclusions that can be drawn from such analyzes are more precise.

Availability and implementation
We implemented a simple web interface that allows the users to analyze a single dose–response dataset, as well as to statistically compare the metrics of two datasets.
Learning a mixture of microbial networks using minorization–maximization
Authors: Tavakoli Sahar , Yooseph Shibu 
Published: May 2019

AbstractMotivationThe interactions among the constituent members of a microbial community play a major role in determining the overall behavior of the community and the abundance levels of its members. These interactions can be modeled using a network whose nodes represent microbial taxa and edges represent pairwise interactions. A microbial network is typically constructed from a sample-taxa count matrix that is obtained by sequencing multiple biological samples and identifying taxa counts. From large-scale microbiome studies, it is evident that microbial community compositions and interactions are impacted by environmental and/or host factors. Thus, it is not unreasonable to expect that a sample-taxa matrix generated as part of a large study involving multiple environmental or clinical parameters can be associated with more than one microbial network. However, to our knowledge, microbial network inference methods proposed thus far assume that the sample-taxa matrix is associated with a single network.ResultsWe present a mixture model framework to address the scenario when the sample-taxa matrix is associated with K microbial networks. This count matrix is modeled using a mixture of K Multivariate Poisson Log-Normal distributions and parameters are estimated using a maximum likelihood framework. Our parameter estimation algorithm is based on the minorization–maximization principle combined with gradient ascent and block updates. Synthetic datasets were generated to assess the performance of our approach on absolute count data, compositional data and normalized data. We also addressed the recovery of sparse networks based on an l1-penalty model.Availability and implementationMixMPLN is implemented in R and is freely available at https://github.com/sahatava/MixMPLN.Supplementary informationSupplementary data are available at Bioinformatics online.
MCS2: minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks
Authors: Miraskarshahi Reza , Zabeti Hooman , Stephen Tamon , Chindelevitch Leonid 
Published: May 2019

Abstract

Motivation
Constraint-based modeling of metabolic networks helps researchers gain insight into the metabolic processes of many organisms, both prokaryotic and eukaryotic. Minimal cut sets (MCSs) are minimal sets of reactions whose inhibition blocks a target reaction in a metabolic network. Most approaches for finding the MCSs in constrained-based models require, either as an intermediate step or as a byproduct of the calculation, the computation of the set of elementary flux modes (EFMs), a convex basis for the valid flux vectors in the network. Recently, Ballerstein et al. proposed a method for computing the MCSs of a network without first computing its EFMs, by creating a dual network whose EFMs are a superset of the MCSs of the original network. However, their dual network is always larger than the original network and depends on the target reaction. Here we propose the construction of a different dual network, which is typically smaller than the original network and is independent of the target reaction, for the same purpose. We prove the correctness of our approach, minimal coordinated support (MCS2), and describe how it can be modified to compute the few smallest MCSs for a given target reaction.

Results
We compare MCS2 to the method of Ballerstein et al. and two other existing methods. We show that MCS2 succeeds in calculating the full set of MCSs in many models where other approaches cannot finish within a reasonable amount of time. Thus, in addition to its theoretical novelty, our approach provides a practical advantage over existing methods.

Availability and implementation
MCS2 is freely available at https://github.com/RezaMash/MCS under the GNU 3.0 license.

Supplementary information
Supplementary data are available at Bioinformatics online.
Weighing up Work Willingness in Social Assistance: A Balancing Act on Multiple Levels
Authors: De Wilde Marjolijn , Marchal Sarah 
Published: May 2019

Abstract
In all European countries, social assistance legislation specifies that the receipt of benefits is conditional upon the willingness to work. Nevertheless, the manner in which such policies are implemented in practice has remained a black box. From the literature on social policy, social work, and social administration, we know that implementation is the result of decisions at multiple levels. To our knowledge, however, this study is the first quantitative attempt to bring together the insights from these various strands of literature into a combined assessment of factors that determine willingness-to-work assessments. We build on an innovative and purpose-designed survey of social workers in Belgium. We identified factors determining the perceptions of 584 case managers, clustered in 89 municipalities, with regard to sanction decisions upon job refusal, based on almost 5,000 experimentally varied client cases (vignette experiment). These unique data make it possible to distinguish between the effects of case managers who assess individual cases and characteristics of the local welfare agencies and municipalities in which they operate. The results reveal relatively little variation between municipalities, which can be largely explained by characteristics of the municipalities (e.g. political ideology and organizational setting). Surprisingly, however, we find extensive variation at the case-manager level. Although some of this variation remains unexplained, a substantial share can be explained by characteristics of individual case managers (e.g. age and attitudes concerning the welfare state). This finding raises concerns about the unintended consequences of the broad discretion granted to case managers within contemporary social assistance schemes.
Associations between Swiss Needle Cast Severity and Foliar Nutrients in Young-Growth Douglas-Fir in Coastal Western Oregon and Southwest Washington, USA
Authors: Lan Yung-Hsiang , Shaw David C , Ritóková Gabriela , Hatten Jeff A 
Published: May 2019

Abstract
Swiss needle cast (SNC) is a foliage disease of Douglas-fir (Pseudotsuga menziesii) caused by Nothophaeocryptopus gaeumannii, an ascomycete fungus (Mycosphaerellaceae) that causes tree growth reductions in the Pacific Northwest. The epidemiology of the fungus is generally well known, but the relations between disease expression and foliar nutrition are unclear. In this study, we used data from the Swiss Needle Cast Cooperative research and monitoring plot network in western Oregon and SW Washington to assess associations between SNC severity, carbon, and nine foliage nutrients (nitrogen, Na, K, P, Ca, Mg, Mn, Al, S). Foliage samples were collected from midcrown of selected Douglas-firs from each plot. SNC severity was determined on 2-year-old needles by multiplying disease incidence and fungal reproductive (pseudothecia) density. Disease severity and nutrient relations were determined using linear mixed models. SNC severity showed statistically significant positive trends with concentrations of carbon, nitrogen, Na, K, and S, no relation with concentrations of Ca, Mg, or Al, and slightly negative trends that were not significant for P and Mn. This is the first such analysis of associations between a conifer foliage disease and foliage nutrients across a landscape; subsequently, there is little published literature on how or why these nutrients may interact with disease.
Longevity-Associated Variant of BPIFB4 Mitigates Monocyte-Mediated Acquired Immune Response
Authors: Ciaglia Elena , Montella Francesco , Maciag Anna , Scala Pasqualina , Ferrario Anna , Banco Carlotta , Carrizzo Albino , Spinelli Chiara Carmela , Cattaneo Monica , De Candia Paola , Vecchione Carmine , Villa Francesco , Puca Annibale Alessandro 
Published: May 2019

Abstract
One of the basis of exceptional longevity is the maintaining of the balance between inflammatory and anti-inflammatory networks. The monocyte-macrophages activation plays a major role in tuning the immune responses, by oscillating between patrolling-protective to inflammatory status. Longevity-associated variant (LAV) of bactericidal/permeability-increasing fold-containing family B member 4 (BPIFB4) activates calcium, PKC-alpha, and eNOS, rescuing endothelial dysfunction in aged mice and inducing revascularization. The BPIFB4’s increment in serum of healthy long-living individuals (LLIs) compared to nonhealthy ones, its therapeutic potential in improving vascular homeostasis, which depends on immune system, together with its expression in bone marrow myeloid cells, suggests that LAV-BPIFB4 may improve immune regulation. Here we show that human monocytes exposed to LAV-BPIFB4 protein increased co-stimulatory molecules in resting state and reduced pro-inflammatory cytokine tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) after activating stimuli. Accordingly, a low percentage of CD69+ activated lymphocytes are found among LAV-BPIFB4-treated peripheral blood mononuclear cells (PBMCs). Moreover, human monocyte-derived dendritic cells (DCs) generated in presence of LAV-BPIFB4 secreted higher anti-(IL-10 and TGF-β) and lower pro-inflammatory (TNF-α and IL-1β) cytokines. Accordingly, LLIs’ plasma showed higher levels of circulating IL-10 and of neutralizing IL-1 receptor antagonist (IL-1RA) compared to controls. Thus, LAV-BPIFB4 effects on myeloid compartment could represent one example of a genetic predisposition carried by LLIs to protect from immunological dysfunctions.