bluuebunny/crossref_metadata_2025 huggingface dataset:
Longitudinal evaluation of SMN levels as biomarker for spinal muscular atrophy: results of a phase IIb double-blind study of salbutamol
Authors: Tiziano Francesco Danilo , Lomastro Rosa , Abiusi Emanuela , Pasanisi Maria Barbara , Di Pietro Lorena , Fiori Stefania , Baranello Giovanni , Angelini Corrado , Sorarù Gianni , Gaiani Alessandra , Mongini Tiziana , Vercelli Liliana , Mercuri Eugenio , Vasco Gessica , Pane Marika , Vita Giuseppe , Vita Gianluca , Messina Sonia , Petillo Roberta , Passamano Luigia , Politano Luisa , Campanella Angela , Mantegazza Renato , Morandi Lucia
Published: December 2018

Background

Spinal muscular atrophy (SMA) is an autosomal recessive neuromuscular disorder, due to the loss of function of the survival motor neuron (SMN1) gene. The first treatment for the condition, recently approved, is based on the reduction of exon 7 skipping in mRNAs produced by a highly homologous gene (SMN2). The primary objective of the present study was to evaluate the applicability of the dosage of SMN gene produts in blood, as biomarker for SMA, and the safety of oral salbutamol, a beta2-adrenergic agonist modulating SMN2 levels.

Methods

We have performed a 1-year multicentre, double-blind, placebo-controlled study with salbutamol in 45 adult patients with SMA. Patients assumed 4 mg of salbutamol or placebo/three times a day. Molecular tests were SMN2 copy number, SMN transcript and protein levels. We have also explored the clinical effect, by the outcome measures available at the time of study design.

Results

Thirty-six patients completed the study. Salbutamol was safe and well tolerated. We observed a significant and progressive increase in SMN2 full-length levels in peripheral blood of the salbutamol-treated patients (p<0.00001). The exploratory analysis of motor function showed an improvement in most patients.

Conclusions

Our data demonstrate safety and molecular efficacy of salbutamol. We provide the first longitudinal evaluation of SMN levels (both transcripts and protein) in placebo and in response to a compound modulating the gene expression: SMN transcript dosage in peripheral blood is reliable and may be used as pharmacodynamic marker in clinical trials with systemic compounds modifying SMN2levels.

Trial registration number

EudraCT no. 2007-001088-32.
Interpersonal violence in peacetime Malawi
Authors: Maine Rebecca G , Williams Brittney , Kincaid Jennifer A , Mulima Gift , Varela Carlos , Gallaher Jared R , Reid Trista D , Charles Anthony G
Published: December 2018

Background

The contribution of interpersonal violence (IPV) to trauma burden varies greatly by region. The high rates of IPV in sub-Saharan Africa are thought to relate in part to the high rates of collective violence. Malawi, a country with no history of internal collective violence, provides an excellent setting to evaluate whether collective violence drives the high rates of IPV in this region.

Methods

This is a retrospective review of a prospective trauma registry from 2009 through 2016 at Kamuzu Central Hospital in Lilongwe, Malawi. Adult (>16 years) victims of IPV were compared with non-intentional trauma victims. Log binomial regression determined factors associated with increased risk of mortality for victims of IPV.

Results

Of 72 488 trauma patients, 25 008 (34.5%) suffered IPV. Victims of IPV were more often male (80.2% vs. 74.8%; p<0.001), younger (median age: 28 years (IQR: 23–34) vs. 30 years (IQR: 24–39); p<0.001), and were more often admitted at night (47.4% vs. 31.9%; p<0.001). Of the IPV victims, 16.5% admitted alcohol use, compared with only 4.4% in other trauma victims (p<0.001). In regression modeling, compared with extremity injuries, head injuries (3.14, 2.24–4.39; p<0.001) and torso injuries (4.32, 2.98–6.27; p<0.001) had increased risk of mortality. Compared with other or unknown mechanisms, penetrating injuries also had increased risk of mortality (1.46, 95% CI 1.17 to 1.81, p=0.001). Alcohol use was associated with a lower risk of mortality (0.54, 95% CI 0.39 to 0.75; p<0.001).

Discussion

Even in a sub-Saharan country that never experienced internal collective violence, IPV injury rates are high. Public health efforts to measure and address alcohol use, and studies to determine the role of “mob justice,” poverty, and intimate partner violence in IPV, in Malawi are needed.

Level of evidence

Level III.
Axions and anomalous U(1)’s
Authors: Bonnefoy Quentin , Dudas Emilian
Published: December 2018

Inspired by recent studies of high-scale decay constant or flavorful QCD axions, we review and clarify their existence in effective string models with anomalous U(1) gauge groups. We find that such models, when coupled to charged scalars getting vacuum expectation values, always have one light axion, whose mass can only come from nonperturbative effects. If the main nonperturbative effect is from QCD, then it becomes a Peccei–Quinn axion candidate for solving the strong CP problem. We then study simple models with universal Green–Schwarz mechanism and only one charged scalar field: in the minimal gaugino condensation case the axion mass is tied to the supersymmetry breaking scale and cannot be light enough, but slightly refined models maintain a massless axion all the way down to the QCD scale. Both kinds of models can be extended to yield intermediate scale axion decay constants. Finally, we gauge flavorful axion models under an anomalous U(1) and discuss the axion couplings which arise.
Tachyon scalar field in a braneworld cosmology
Authors: Dimitrijevic Dragoljub D. , Bilić Neven , Djordjevic Goran S. , Milosevic Milan , Stojanovic Marko
Published: December 2018

We analyze a tachyon cosmological model based on the dynamics of a 3-brane in the bulk of the second Randall–Sundrum model. This model contains extended general warp functions, i.e. generalized bulk geometry. We study a power law warp factor in cosmological context. This type of warp factor generates an inverse power law tachyonic potential.
New orbitals probes of ultra-light dark matter
Authors: Blas Diego
Published: December 2018

I will discuss how to use precision data from orbital motion of binary pulsars to constrain models of ultra-light dark matter (masses in the range [Formula: see text] eV to [Formula: see text] eV).
Factors Affecting Entrepreneurial Behavior Among Employees in Organizations: Mediating Role of Affective Commitment
Authors: ul Haq Muhammad Anwar , Jingdong Yan , Usman Muhammad , Khalid Shaista
Published: December 2018

This paper finds the role of perceived failure tolerance, communication openness, work discretion, and reward fairness in influencing the entrepreneurial behavior of employees. We also study the mediating role of affective commitment between entrepreneurial behavior and its antecedents. Data were collected using survey design from 381 telecommunication professionals in Pakistan. The analysis, using SEM, shows that predictor variables have a significant positive influence on organizational entrepreneurial behavior. Furthermore, affective commitment partially mediates the relationship between failure tolerance, communication openness, work discretion and organizational entrepreneurial behavior, whereas, it fully mediates the effect of reward fairness. On the basis of our results, managers are advised to lead their followers in such a way that the employees offer their innovative potential for the organization by becoming internal entrepreneurs.
TAp73 Modifies Metabolism and Positively Regulates Growth of Cancer Stem–Like Cells in a Redox-Sensitive Manner
Authors: Sharif Tanveer , Dai Cathleen , Martell Emma , Ghassemi-Rad Mohammad Saleh , Hanes Mark Robert , Murphy Patrick J. , Kennedy Barry E. , Venugopal Chitra , Subapanditha Minomi , Giacomantonio Carman A. , Marcato Paola , Singh Sheila K. , Gujar Shashi
Published: December 2018

Purpose:

Stem-like cancer cells, with characteristic self-renewal abilities, remain highly refractory to various clinical interventions. As such, stemness-inhibiting entities, such as tumor suppressor p53, are therapeutically pursued for their anticancer activities. Interestingly, similar implications for tumor suppressor TAp73 in regulating stemness features within stem-like cancer cells remain unknown.

Experimental Design: This study utilizes various in vitro molecular biology techniques, including immunoblotting, qRT-PCR, and mass spectrometry–based proteomics, and metabolomics approaches to study the role of TAp73 in human and murine embryonal carcinoma stem-like cells (ECSLC) as well as human breast cancer stem-like cells (BCSLC). These findings were confirmed using patient-derived brain tumor–initiating cells (BTIC) and in vivo xenograft models.

Results:

TAp73 inhibition decreases the expression of stem cell transcription factors Oct4, Nanog, and Sox-2, as well as tumorsphere formation capacity in ECSLCs. In vivo, TAp73-deficient ECSLCs and BCSLCs demonstrate decreased tumorigenic potential when xenografted in mice. Mechanistically, TAp73 modifies the proline regulatory axis through regulation of enzymes GLS, OAT, and PYCR1 involved in the interconversion of proline–glutamine–ornithine. Further, TAp73 deficiency exacerbates glutamine dependency, enhances accumulation of reactive oxygen species through reduced superoxide dismutase 1 (SOD1) expression, and promotes differentiation by arresting cell cycle and elevating autophagy. Most importantly, the knockdown of TAp73 in CD133HI BTICs, separated from three different glioblastoma patients, strongly decreases the expression of prosurvival factors Sox-2, BMI-1, and SOD1, and profoundly decreases their self-renewal capacity as evidenced through their reduced tumorsphere formation ability.

Conclusions:

Collectively, we reveal a clinically relevant aspect of cancer cell growth and stemness regulation through TAp73-mediated redox-sensitive metabolic reprogramming.
Of Microbes and Microsatellites
Authors: Atreya Chloe E. , Venook Alan P.
Published: December 2018

A ubiquitous oral cavity microbe, Fusobacterium nucleatum, is increasingly being implicated in colorectal cancer pathogenesis. An article in this issue elucidates the differential association of F. nucleatum with tumor-infiltrating lymphocytes depending on microsatellite instability status. Cancer Immunol Res; 6(11); 1290–1. ©2018 AACR.

See article by Hamada et al., p. 1327.
Fine-Tuning of Sox17 and Canonical Wnt Coordinates the Permeability Properties of the Blood-Brain Barrier
Authors: Corada Monica , Orsenigo Fabrizio , Bhat Ganesh Parameshwar , Conze Lei Liu , Breviario Ferruccio , Cunha Sara Isabel , Claesson-Welsh Lena , Beznoussenko Galina V. , Mironov Alexander A. , Bacigaluppi Marco , Martino Gianvito , Pitulescu Mara E. , Adams Ralf H. , Magnusson Peetra , Dejana Elisabetta
Published: December 2018

Rationale:

The microvasculature of the central nervous system includes the blood-brain barrier (BBB), which regulates the permeability to nutrients and restricts the passage of toxic agents and inflammatory cells. Canonical Wnt/β-catenin signaling is responsible for the early phases of brain vascularization and BBB differentiation. However, this signal declines after birth, and other signaling pathways able to maintain barrier integrity at postnatal stage are still unknown.

Objective:

Sox17 (SRY [sex-determining region Y]-box 17) constitutes a major downstream target of Wnt/β-catenin in endothelial cells and regulates arterial differentiation. In the present article, we asked whether Sox17 may act downstream of Wnt/β-catenin in inducing BBB differentiation and maintenance.

Methods and Results:

Using reporter mice and nuclear staining of Sox17 and β-catenin, we report that although β-catenin signaling declines after birth, Sox17 activation increases and remains high in the adult. Endothelial-specific inactivation of Sox17 leads to increase of permeability of the brain microcirculation. The severity of this effect depends on the degree of BBB maturation: it is strong in the embryo and progressively declines after birth. In search of Sox17 mechanism of action, RNA sequencing analysis of gene expression of brain endothelial cells has identified members of the Wnt/β-catenin signaling pathway as downstream targets of Sox17. Consistently, we found that Sox17 is a positive inducer of Wnt/β-catenin signaling, and it acts in concert with this pathway to induce and maintain BBB properties. In vivo, inhibition of the β-catenin destruction complex or expression of a degradation-resistant β-catenin mutant, prevent the increase in permeability and retina vascular malformations observed in the absence of Sox17.

Conclusions:

Our data highlight a novel role for Sox17 in the induction and maintenance of the BBB, and they underline the strict reciprocal tuning of this transcription factor and Wnt/β-catenin pathway. Modulation of Sox17 activity may be relevant to control BBB permeability in pathological conditions.
Aggregation of Child Cardiac Progenitor Cells Into Spheres Activates Notch Signaling and Improves Treatment of Right Ventricular Heart Failure
Authors: Trac David , Maxwell Joshua T. , Brown Milton E. , Xu Chunhui , Davis Michael E.
Published: December 2018

Rationale:

Congenital heart disease can lead to life-threatening right ventricular (RV) heart failure. Results from clinical trials support expanding cardiac progenitor cell (CPC) based therapies. However, our recent data show that CPCs lose function as they age, starting as early as 1 year.

Objective:

To determine whether the aggregation of child (1–5-year-old) CPCs into scaffold-free spheres can improve differentiation by enhancing Notch signaling, a known regulator of CPC fate. We hypothesized that aggregated (3-dimensional [3D]) CPCs will repair RV heart failure better than monolayer (2-dimensional [2D]) CPCs.

Methods and Results:

Spheres were produced with 1500 CPCs each using a microwell array. CPC aggregation significantly increased gene expression of Notch1 compared with 2D CPCs, accompanied by significant upregulation of cardiogenic transcription factors (GATA4, HAND1, MEF2C, NKX2.5, and TBX5) and endothelial markers (CD31, FLK1, FLT1, VWF). Blocking Notch receptor activation with the γ-secretase inhibitor DAPT (N-[N-(3,5-difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester) diminished these effects. To evaluate the therapeutic improvements of CPC aggregation, RV heart failure was induced in athymic rats by pulmonary artery banding, and cells were implanted into the RV free wall. Echocardiographic measurements 28 days postimplantation showed significantly improved RV function with 3D compared with 2D CPCs. Tracking implanted CPCs via DiR (1,1’-dioctadecyl-3,3,3’,3’-tetramethylindotricarbocyanine iodide)-labeling showed improved retention of 3D CPCs. Transducing 3D CPCs with Notch1-shRNA (short hairpin RNA) did not reduce retention, but significantly reduced RV functional improvements. Histological analyses showed 3D treatment reduced RV fibrosis and increased angiogenesis. Although 3D CPCs formed CD31
+
vessel-like cells in vivo, these effects are more likely because of improved 3D CPC exosome function compared with 2D CPC exosomes.

Conclusions:

Spherical aggregation improves child CPC function in a Notch-dependent manner. The strong reparative ability of CPC spheres warrants further investigation as a treatment for pediatric heart failure, especially in older children where reparative ability may be reduced.
Evaluation of Macitentan in Patients With Eisenmenger Syndrome
Authors: Gatzoulis Michael A. , Landzberg Michael , Beghetti Maurice , Berger Rolf M. , Efficace Michela , Gesang Sophie , He Jian’guo , Papadakis Kelly , Pulido Tomás , Galiè Nazzareno ,   On behalf of the MAESTRO Study Investigators
Published: December 2018

Background:

Eisenmenger syndrome describes congenital heart disease-associated severe pulmonary hypertension accompanied by right-to-left shunting. The multicenter, double-blind, randomized, placebo-controlled, 16-week, phase III MAESTRO study (Macitentan in Eisenmenger Syndrome to Restore Exercise Capacity) evaluated the efficacy and safety of the endothelin receptor antagonist macitentan in patients with Eisenmenger syndrome.

Methods:

Patients with Eisenmenger syndrome aged ≥12 years and in World Health Organization functional class II–III were randomized 1:1 to placebo or macitentan 10 mg once daily for 16 weeks. Patients with complex cardiac defects, Down syndrome and background PAH therapy were eligible. The primary end point was change from baseline to week 16 in 6-minute walk distance. Secondary end points included change from baseline to week 16 in World Health Organization functional class. Exploratory end points included NT-proBNP (N-terminal pro-B-type natriuretic peptide) at end of treatment expressed as a percentage of baseline. In a hemodynamic substudy, exploratory end points included pulmonary vascular resistance index (PVRi) at week 16 as a percentage of baseline.

Results:

Two hundred twenty six patients (macitentan n=114; placebo n=112) were randomized. At baseline, 60% of patients were in World Health Organization functional class II and 27% were receiving phosphodiesterase type-5 inhibitors. At week 16, the mean change from baseline in 6-minute walk distance was 18.3 m and 19.7 m in the macitentan and placebo groups (least-squares mean difference, -4.7 m; 95% confidence limit (CL), -22.8, 13.5;
P
=0.612). World Health Organization functional class improved from baseline to week 16 in 8.8% and 14.3% of patients in the macitentan and placebo groups (odds ratio, 0.53; 95% CL, 0.23, 1.24). NT-proBNP levels decreased with macitentan versus placebo (ratio of geometric means, 0.80; 95% CL, 0.68, 0.94). In the hemodynamic substudy (n=39 patients), macitentan decreased PVRi compared with placebo (ratio of geometric means, 0.87; 95% CL, 0.73, 1.03). The most common adverse events with macitentan versus placebo were headache (11.4 versus 4.5%) and upper respiratory tract infection (9.6 versus 6.3%); a hemoglobin decrease from baseline of ≥2 g/dL occurred in 36.0% versus 8.9% of patients. Five patients (3 macitentan; 2 placebo) prematurely discontinued treatment and 1 patient died (macitentan group).

Conclusions:

Macitentan did not show superiority over placebo on the primary end point of change from baseline to week 16 in exercise capacity in patients with Eisenmenger syndrome.

Clinical Trial Registration:

URL:
https://www.clinicaltrials.gov
. Unique identifier: NCT01743001.
Glycolytic Switch Is Required for Transdifferentiation to Endothelial Lineage
Authors: Lai Li , Reineke Erin , Hamilton Dale J. , Cooke John P.
Published: December 2018

Background:

We have previously shown that activation of cell-autonomous innate immune signaling facilitates the transdifferentiation of fibroblasts into induced endothelial cells, and is required to generate induced endothelial cells with high fidelity for endothelial lineage. Recent studies indicate that a glycolytic switch plays a role in induced pluripotent stem cell generation from somatic cells.

Methods:

Seahorse and metabolomics flux assays were used to measure the metabolic changes during transdifferentiation in vitro, and Matrigel plug assay was used to assess the effects of glycolysis modulators on transdifferentiation in vivo.

Results:

The metabolic switch begins rapidly after activation of innate immunity, before the expression of markers of endothelial lineage. Inhibiting glycolysis impaired, whereas facilitating glycolysis enhanced, the generation of induced endothelial cells. The toll-like receptor 3 agonist poly I:C increased expression of the mitochondrial citrate transporter Slc25A1, and the nuclear ATP-citrate lyase, in association with intracellular accumulation of citrate, the precursor for acetyl coenzyme A. These metabolic changes were coordinated with increased histone acetylation during transdifferentiation.

Conclusion:

Innate immune signaling promotes a glycolytic switch that is required for transdifferentiation, both processes being attenuated by ATP-citrate lyase knockdown. These data shed light on a novel link between metabolism and epigenetic modulation in transdifferentiation.
Randomized All-Comers Evaluation of a Permanent Polymer Zotarolimus-Eluting Stent Versus a Polymer-Free Amphilimus-Eluting Stent
Authors: Rozemeijer Rik , Stein Mera , Voskuil Michiel , van den Bor Rutger , Frambach Peter , Pereira Bruno , Koudstaal Stefan , Leenders Geert E. , Timmers Leo , Rittersma Saskia Z. , Kraaijeveld Adriaan O. , Agostoni Pierfrancesco , Roes Kit C. , Doevendans Pieter A. , Stella Pieter R. ,   For the ReCre8 Study Investigators
Published: December 2018

Background:

Polymer-free amphilimus-eluting stents (PF-AES) represent a novel elution technology in the current era of drug-eluting stents. The clinical safety and efficacy of PF-AES as compared with latest-generation permanent-polymer zotarolimus-eluting stents (PP-ZES) have not yet been investigated in a large randomized trial.

Methods:

In this physician-initiated, prospective, multicenter, randomized, noninferiority trial, an all-comers population requiring percutaneous coronary intervention was enrolled across 3 European sites. Randomization (1:1 ratio) to PP-ZES or PF-AES was performed after stratification for troponin status and diabetes mellitus. In both treatment arms, troponin-positive patients were planned for 12-month dual antiplatelet therapy, whereas troponin-negative patients were planned for 1-month dual antiplatelet therapy. Outcome assessors were blinded to the allocated treatment. The device-oriented primary end point of target-lesion failure was defined as cardiac death, target-vessel myocardial infarction, or target-lesion revascularization at 12-months as analyzed by modified intention-to-treat (80% power, and a 3.5% noninferiority margin).

Results:

In total, 1502 patients were randomized and 1491 treated with the assigned stent and available for follow-up. The primary end point occurred in 42 (5.6%) of the 744 patients receiving PP-ZES versus 46 (6.2%) of the 747 patients receiving PF-AES. PF-AES were clinically noninferior to PP-ZES (risk difference, 0.5%; upper limit 1-sided 95% confidence interval, 2.6%;
P
noninferiority
=0.0086). Cardiac death occurred in 10 (1.3%) versus 10 patients (1.3%;
P
value for difference, 1.00), target-vessel myocardial infarction occurred in 18 (2.4%) versus 17 patients (2.3%;
P
value for difference, 0.87), and target-lesion revascularization occurred in 22 (2.9%) versus 20 patients (2.6%;
P
value for difference, 0.75) for PF-AES as compared with PP-ZES. Overall, definite or probable stent thrombosis occurred in 1.0%.

Conclusions:

PF-AES were noninferior to PP-ZES regarding target-lesion failure at 12 months. Findings regarding the secondary end point and prespecified subgroups were generally consistent with that of the primary end point.

Clinical Trial Registration:

URL:
https://www.clinicaltrials.gov
. Unique identifier: NCT02328898.
Sex Differences in Severity of Stroke in the INSTRUCT Study: a Meta‐Analysis of Individual Participant Data
Authors: Phan Hoang T. , Reeves Mathew J. , Blizzard Christopher L. , Thrift Amanda G. , Cadilhac Dominique A. , Sturm Jonathan , Otahal Petr , Rothwell Peter , Bejot Yannick , Cabral Norberto L. , Appelros Peter , Kõrv Janika , Vibo Riina , Minelli Cesar , Gall Seana L.
Published: December 2018

Background

Women have worse outcomes after stroke than men, and this may be partly explained by stroke severity. We examined factors contributing to sex differences in severity of acute stroke assessed by the National Institutes of Health Stroke Scale.

Methods and Results

We pooled individual participant data with National Institutes of Health Stroke Scale assessment (N=6343) from 8 population‐based stroke incidence studies (1996–2014), forming part of INSTRUCT (International Stroke Outcomes Study). Information on sociodemographics, stroke‐related clinical factors, comorbidities, and pre‐stroke function were obtained. Within each study, relative risk regression using log‐binominal modeling was used to estimate the female:male relative risk (
RR
) of more severe stroke (National Institutes of Health Stroke Scale>7) stratified by stroke type (ischemic stroke and intracerebral hemorrhage). Study‐specific unadjusted and adjusted
RR
s, controlling for confounding variables, were pooled using random‐effects meta‐analysis. National Institutes of Health Stroke Scale data were recorded in 5326 (96%) of 5570 cases with ischemic stroke and 773 (90%) of 855 participants with intracerebral hemorrhage. The pooled unadjusted female:male
RR
for severe ischemic stroke was 1.35 (95%
CI
1.24–1.46). The sex difference in severity was attenuated after adjustment for age, pre‐stroke dependency, and atrial fibrillation but remained statistically significant (pooled
RR
adjusted
1.20, 95%
CI
1.10–1.30). There was no sex difference in severity for intracerebral hemorrhage (
RR
crude
1.08, 95%
CI
0.97–1.21;
RR
adjusted
1.08, 95%
CI
0.96–1.20).

Conclusions

Although women presented with more severe ischemic stroke than men, much although not all of the difference was explained by pre‐stroke factors. Sex differences could potentially be ameliorated by strategies to improve pre‐stroke health in the elderly, the majority of whom are women. Further research on the potential biological origin of sex differences in stroke severity may also be warranted.
LUCAS Versus Manual Chest Compression During Ambulance Transport: A Hemodynamic Study in a Porcine Model of Cardiac Arrest
Authors: Magliocca Aurora , Olivari Davide , De Giorgio Daria , Zani Davide , Manfredi Martina , Boccardo Antonio , Cucino Alberto , Sala Giulia , Babini Giovanni , Ruggeri Laura , Novelli Deborah , Skrifvars Markus B , Hardig Bjarne Madsen , Pravettoni Davide , Staszewsky Lidia , Latini Roberto , Belloli Angelo , Ristagno Giuseppe
Published: December 2018

Background

Mechanical chest compression (CC) is currently suggested to deliver sustained high‐quality CC in a moving ambulance. This study compared the hemodynamic support provided by a mechanical piston device or manual CC during ambulance transport in a porcine model of cardiopulmonary resuscitation.

Methods and Results

In a simulated urban ambulance transport, 16 pigs in cardiac arrest were randomized to 18 minutes of mechanical CC with the LUCAS (n=8) or manual CC (n=8). ECG, arterial and right atrial pressure, together with end‐tidal CO
2
and transthoracic impedance curve were continuously recorded. Arterial lactate was assessed during cardiopulmonary resuscitation and after resuscitation. During the initial 3 minutes of cardiopulmonary resuscitation, the ambulance was stationary, while then proceeded along a predefined itinerary. When the ambulance was stationary, CC‐generated hemodynamics were equivalent in the 2 groups. However, during ambulance transport, arterial and coronary perfusion pressure, and end‐tidal CO
2
were significantly higher with mechanical CC compared with manual CC (coronary perfusion pressure: 43±4 versus 18±4 mmHg; end‐tidal CO
2
: 31±2 versus 19±2 mmHg,
P
<0.01 at 18 minutes). During cardiopulmonary resuscitation, arterial lactate was lower with mechanical CC compared with manual CC (6.6±0.4 versus 8.2±0.5 mmol/L,
P
<0.01). During transport, mechanical CC showed greater constancy compared with the manual CC, as represented by a higher CC fraction and a lower transthoracic impedance curve variability (
P
<0.01). All animals in the mechanical CC group and 6 (75%) in the manual one were successfully resuscitated.

Conclusions

This model adds evidence in favor of the use of mechanical devices to provide ongoing high‐quality CC and tissue perfusion during ambulance transport.
Death From Stroke in End-Stage Kidney Disease
Authors: De La Mata Nicole L. , Masson Philip , Al-Shahi Salman Rustam , Kelly Patrick J. , Webster Angela C.
Published: December 2018

Background and Purpose—

People with end-stage kidney disease (ESKD) are at greater risk of stroke. We aimed to compare stroke mortality between the ESKD population and the general population.

Methods—

We included all patients with incident ESKD in Australia, 1980 to 2013, and New Zealand, 1988 to 2012. The primary cause of death was ascertained using data linkage with national death registers. We produced standardized mortality ratios for stroke deaths, by age, sex, and calendar year.

Results—

We included 60 823 patients with ESKD, where 941 stroke deaths occurred during 381 874 person-years. Patients with ESKD had >3× the stroke deaths compared with the general population (standardized mortality ratio, 3.4; 95% CI, 3.2–3.6), markedly higher in younger people and women. The greatest excess was in intracerebral hemorrhages (standardized mortality ratio, 5.2; 95% CI, 4.5–5.9). Excess stroke deaths in patients with ESKD decreased over time, although were still double in 2013 (2013 standardized mortality ratio, 2.1; 95% CI, 1.5–2.9).

Conclusions—

People with ESKD experience much greater stroke mortality with the greatest difference for women and younger people. However, mortality has improved over time.
Visually Grounded and Textual Semantic Models Differentially Decode Brain Activity Associated with Concrete and Abstract Nouns
Authors: Anderson Andrew J. , Kiela Douwe , Clark Stephen , Poesio Massimo
Published: December 2018

Important advances have recently been made using computational semantic models to decode brain activity patterns associated with concepts; however, this work has almost exclusively focused on concrete nouns. How well these models extend to decoding abstract nouns is largely unknown. We address this question by applying state-of-the-art computational models to decode functional Magnetic Resonance Imaging (fMRI) activity patterns, elicited by participants reading and imagining a diverse set of both concrete and abstract nouns. One of the models we use is linguistic, exploiting the recent word2vec skipgram approach trained on Wikipedia. The second is visually grounded, using deep convolutional neural networks trained on Google Images. Dual coding theory considers concrete concepts to be encoded in the brain both linguistically and visually, and abstract concepts only linguistically. Splitting the fMRI data according to human concreteness ratings, we indeed observe that both models significantly decode the most concrete nouns; however, accuracy is significantly greater using the text-based models for the most abstract nouns. More generally this confirms that current computational models are sufficiently advanced to assist in investigating the representational structure of abstract concepts in the brain.
A Polynomial-Time Dynamic Programming Algorithm for Phrase-Based Decoding with a Fixed Distortion Limit
Authors: Chang Yin-Wen , Collins Michael
Published: December 2018

Decoding of phrase-based translation models in the general case is known to be NP-complete, by a reduction from the traveling salesman problem (Knight, 1999). In practice, phrase-based systems often impose a hard distortion limit that limits the movement of phrases during translation. However, the impact on complexity after imposing such a constraint is not well studied. In this paper, we describe a dynamic programming algorithm for phrase-based decoding with a fixed distortion limit. The runtime of the algorithm is O( nd! lh d+1) where n is the sentence length, d is the distortion limit, l is a bound on the number of phrases starting at any position in the sentence, and h is related to the maximum number of target language translations for any source word. The algorithm makes use of a novel representation that gives a new perspective on decoding of phrase-based models.
Automatically Tagging Constructions of Causation and Their Slot-Fillers
Authors: Dunietz Jesse , Levin Lori , Carbonell Jaime
Published: December 2018

This paper explores extending shallow semantic parsing beyond lexical-unit triggers, using causal relations as a test case. Semantic parsing becomes difficult in the face of the wide variety of linguistic realizations that causation can take on. We therefore base our approach on the concept of constructions from the linguistic paradigm known as Construction Grammar (CxG). In CxG, a construction is a form/function pairing that can rely on arbitrary linguistic and semantic features. Rather than codifying all aspects of each construction’s form, as some attempts to employ CxG in NLP have done, we propose methods that offload that problem to machine learning. We describe two supervised approaches for tagging causal constructions and their arguments. Both approaches combine automatically induced pattern-matching rules with statistical classifiers that learn the subtler parameters of the constructions. Our results show that these approaches are promising: they significantly outperform naïve baselines for both construction recognition and cause and effect head matches.
Fine-Grained Prediction of Syntactic Typology: Discovering Latent Structure with Supervised Learning
Authors: Wang Dingquan , Eisner Jason
Published: December 2018

We show how to predict the basic word-order facts of a novel language given only a corpus of part-of-speech (POS) sequences. We predict how often direct objects follow their verbs, how often adjectives follow their nouns, and in general the directionalities of all dependency relations. Such typological properties could be helpful in grammar induction. While such a problem is usually regarded as unsupervised learning, our innovation is to treat it as supervised learning, using a large collection of realistic synthetic languages as training data. The supervised learner must identify surface features of a language’s POS sequence (hand-engineered or neural features) that correlate with the language’s deeper structure (latent trees). In the experiment, we show: 1) Given a small set of real languages, it helps to add many synthetic languages to the training data. 2) Our system is robust even when the POS sequences include noise. 3) Our system on this task outperforms a grammar induction baseline by a large margin.
Nonparametric Bayesian Semi-supervised Word Segmentation
Authors: Fujii Ryo , Domoto Ryo , Mochihashi Daichi
Published: December 2018

This paper presents a novel hybrid generative/discriminative model of word segmentation based on nonparametric Bayesian methods. Unlike ordinary discriminative word segmentation which relies only on labeled data, our semi-supervised model also leverages a huge amounts of unlabeled text to automatically learn new “words”, and further constrains them by using a labeled data to segment non-standard texts such as those found in social networking services.

Specifically, our hybrid model combines a discriminative classifier (CRF; Lafferty et al. (2001) and unsupervised word segmentation (NPYLM; Mochihashi et al. (2009)), with a transparent exchange of information between these two model structures within the semi-supervised framework (JESS-CM; Suzuki and Isozaki (2008)). We confirmed that it can appropriately segment non-standard texts like those in Twitter and Weibo and has nearly state-of-the-art accuracy on standard datasets in Japanese, Chinese, and Thai.
Winning on the Merits: The Joint Effects of Content and Style on Debate Outcomes
Authors: Wang Lu , Beauchamp Nick , Shugars Sarah , Qin Kechen
Published: December 2018

Debate and deliberation play essential roles in politics and government, but most models presume that debates are won mainly via superior style or agenda control. Ideally, however, debates would be won on the merits, as a function of which side has the stronger arguments. We propose a predictive model of debate that estimates the effects of linguistic features and the latent persuasive strengths of different topics, as well as the interactions between the two. Using a dataset of 118 Oxford-style debates, our model’s combination of content (as latent topics) and style (as linguistic features) allows us to predict audience-adjudicated winners with 74% accuracy, significantly outperforming linguistic features alone (66%). Our model finds that winning sides employ stronger arguments, and allows us to identify the linguistic features associated with strong or weak arguments.
Sparse Coding of Neural Word Embeddings for Multilingual Sequence Labeling
Authors: Berend Gáabor
Published: December 2018

In this paper we propose and carefully evaluate a sequence labeling framework which solely utilizes sparse indicator features derived from dense distributed word representations. The proposed model obtains (near) state-of-the art performance for both part-of-speech tagging and named entity recognition for a variety of languages. Our model relies only on a few thousand sparse coding-derived features, without applying any modification of the word representations employed for the different tasks. The proposed model has favorable generalization properties as it retains over 89.8% of its average POS tagging accuracy when trained at 1.2% of the total available training data, i.e. 150 sentences per language.
Learning to Prune: Exploring the Frontier of Fast and Accurate Parsing
Authors: Vieira Tim , Eisner Jason
Published: December 2018

Pruning hypotheses during dynamic programming is commonly used to speed up inference in settings such as parsing. Unlike prior work, we train a pruning policy under an objective that measures end-to-end performance: we search for a fast and accurate policy. This poses a difficult machine learning problem, which we tackle with the lols algorithm. lols training must continually compute the effects of changing pruning decisions: we show how to make this efficient in the constituency parsing setting, via dynamic programming and change propagation algorithms. We find that optimizing end-to-end performance in this way leads to a better Pareto frontier—i.e., parsers which are more accurate for a given runtime.
Cross-Lingual Syntactic Transfer with Limited Resources
Authors: Rasooli Mohammad Sadegh , Collins Michael
Published: December 2018

We describe a simple but effective method for cross-lingual syntactic transfer of dependency parsers, in the scenario where a large amount of translation data is not available. This method makes use of three steps: 1) a method for deriving cross-lingual word clusters, which can then be used in a multilingual parser; 2) a method for transferring lexical information from a target language to source language treebanks; 3) a method for integrating these steps with the density-driven annotation projection method of Rasooli and Collins (2015). Experiments show improvements over the state-of-the-art in several languages used in previous work, in a setting where the only source of translation data is the Bible, a considerably smaller corpus than the Europarl corpus used in previous work. Results using the Europarl corpus as a source of translation data show additional improvements over the results of Rasooli and Collins (2015). We conclude with results on 38 datasets from the Universal Dependencies corpora.
Overcoming Language Variation in Sentiment Analysis with Social Attention
Authors: Yang Yi , Eisenstein Jacob
Published: December 2018

Variation in language is ubiquitous, particularly in newer forms of writing such as social media. Fortunately, variation is not random; it is often linked to social properties of the author. In this paper, we show how to exploit social networks to make sentiment analysis more robust to social language variation. The key idea is linguistic homophily: the tendency of socially linked individuals to use language in similar ways. We formalize this idea in a novel attention-based neural network architecture, in which attention is divided among several basis models, depending on the author’s position in the social network. This has the effect of smoothing the classification function across the social network, and makes it possible to induce personalized classifiers even for authors for whom there is no labeled data or demographic metadata. This model significantly improves the accuracies of sentiment analysis on Twitter and on review data.
Unsupervised Acquisition of Comprehensive Multiword Lexicons using Competition in an n-gram Lattice
Authors: Brooke Julian , Šnajder Jan , Baldwin Timothy
Published: December 2018

We present a new model for acquiring comprehensive multiword lexicons from large corpora based on competition among n-gram candidates. In contrast to the standard approach of simple ranking by association measure, in our model n-grams are arranged in a lattice structure based on subsumption and overlap relationships, with nodes inhibiting other nodes in their vicinity when they are selected as a lexical item. We show how the configuration of such a lattice can be optimized tractably, and demonstrate using annotations of sampled n-grams that our method consistently outperforms alternatives by at least 0.05 F-score across several corpora and languages.
Phrase Table Induction Using In-Domain Monolingual Data for Domain Adaptation in Statistical Machine Translation
Authors: Marie Benjamin , Fujita Atsushi
Published: December 2018

We present a new framework to induce an in-domain phrase table from in-domain monolingual data that can be used to adapt a general-domain statistical machine translation system to the targeted domain. Our method first compiles sets of phrases in source and target languages separately and generates candidate phrase pairs by taking the Cartesian product of the two phrase sets. It then computes inexpensive features for each candidate phrase pair and filters them using a supervised classifier in order to induce an in-domain phrase table. We experimented on the language pair English–French, both translation directions, in two domains and obtained consistently better results than a strong baseline system that uses an in-domain bilingual lexicon. We also conducted an error analysis that showed the induced phrase tables proposed useful translations, especially for words and phrases unseen in the parallel data used to train the general-domain baseline system.
Joint Prediction of Word Alignment with Alignment Types
Authors: Bigvand Anahita Mansouri , Bu Te , Sarkar Anoop
Published: December 2018

Current word alignment models do not distinguish between different types of alignment links. In this paper, we provide a new probabilistic model for word alignment where word alignments are associated with linguistically motivated alignment types. We propose a novel task of joint prediction of word alignment and alignment types and propose novel semi-supervised learning algorithms for this task. We also solve a sub-task of predicting the alignment type given an aligned word pair. In our experimental results, the generative models we introduce to model alignment types significantly outperform the models without alignment types.
Morpho-syntactic Lexicon Generation Using Graph-based Semi-supervised Learning
Authors: Faruqui Manaal , McDonald Ryan , Soricut Radu
Published: December 2018

Morpho-syntactic lexicons provide information about the morphological and syntactic roles of words in a language. Such lexicons are not available for all languages and even when available, their coverage can be limited. We present a graph-based semi-supervised learning method that uses the morphological, syntactic and semantic relations between words to automatically construct wide coverage lexicons from small seed sets. Our method is language-independent, and we show that we can expand a 1000 word seed lexicon to more than 100 times its size with high quality for 11 languages. In addition, the automatically created lexicons provide features that improve performance in two downstream tasks: morphological tagging and dependency parsing.
Detecting Cross-Cultural Differences Using a Multilingual Topic Model
Authors: Gutiérrez E.D. , Shutova Ekaterina , Lichtenstein Patricia , de Melo Gerard , Gilardi Luca
Published: December 2018

Understanding cross-cultural differences has important implications for world affairs and many aspects of the life of society. Yet, the majority of text-mining methods to date focus on the analysis of monolingual texts. In contrast, we present a statistical model that simultaneously learns a set of common topics from multilingual, non-parallel data and automatically discovers the differences in perspectives on these topics across linguistic communities. We perform a behavioural evaluation of a subset of the differences identified by our model in English and Spanish to investigate their psychological validity.
Decoding Anagrammed Texts Written in an Unknown Language and Script
Authors: Hauer Bradley , Kondrak Grzegorz
Published: December 2018

Algorithmic decipherment is a prime example of a truly unsupervised problem. The first step in the decipherment process is the identification of the encrypted language. We propose three methods for determining the source language of a document enciphered with a monoalphabetic substitution cipher. The best method achieves 97% accuracy on 380 languages. We then present an approach to decoding anagrammed substitution ciphers, in which the letters within words have been arbitrarily transposed. It obtains the average decryption word accuracy of 93% on a set of 50 ciphertexts in 5 languages. Finally, we report the results on the Voynich manuscript, an unsolved fifteenth century cipher, which suggest Hebrew as the language of the document.
Adapting to All Domains at Once: Rewarding Domain Invariance in SMT
Authors: Cuong Hoang , Sima’an Khalil , Titov Ivan
Published: December 2018

Existing work on domain adaptation for statistical machine translation has consistently assumed access to a small sample from the test distribution (target domain) at training time. In practice, however, the target domain may not be known at training time or it may change to match user needs. In such situations, it is natural to push the system to make safer choices, giving higher preference to domain-invariant translations, which work well across domains, over risky domain-specific alternatives. We encode this intuition by (1) inducing latent subdomains from the training data only; (2) introducing features which measure how specialized phrases are to individual induced sub-domains; (3) estimating feature weights on out-of-domain data (rather than on the target domain). We conduct experiments on three language pairs and a number of different domains. We observe consistent improvements over a baseline which does not explicitly reward domain invariance.
Reassessing the Goals of Grammatical Error Correction: Fluency Instead of Grammaticality
Authors: Sakaguchi Keisuke , Napoles Courtney , Post Matt , Tetreault Joel
Published: December 2018

The field of grammatical error correction (GEC) has grown substantially in recent years, with research directed at both evaluation metrics and improved system performance against those metrics. One unvisited assumption, however, is the reliance of GEC evaluation on error-coded corpora, which contain specific labeled corrections. We examine current practices and show that GEC’s reliance on such corpora unnaturally constrains annotation and automatic evaluation, resulting in (a) sentences that do not sound acceptable to native speakers and (b) system rankings that do not correlate with human judgments. In light of this, we propose an alternate approach that jettisons costly error coding in favor of unannotated, whole-sentence rewrites. We compare the performance of existing metrics over different gold-standard annotations, and show that automatic evaluation with our new annotation scheme has very strong correlation with expert rankings (ρ = 0.82). As a result, we advocate for a fundamental and necessary shift in the goal of GEC, from correcting small, labeled error types, to producing text that has native fluency.