bluuebunny/crossref_metadata_2025_split huggingface dataset:
The comments of voices on the appearance of patients with psychosis: ‘the voices tell me that I am ugly’
Authors: Waite Felicity , Diamond Rowan , Collett Nicola , Chadwick Eleanor , Bold Emily , Teale Ashley-Louise , Taylor Kathryn M. , Kirkham Miriam , Twivy Eve , Causier Chiara , Carr Lydia , Bird Jessica C. , Černis Emma , Isham Louise , Freeman Daniel 
Published: September 2019

Background
There are high rates of obesity and low self-esteem in patients with psychosis. The occurrence of negative voice content directly about appearance is therefore plausible. Derogatory comments about appearance are likely to be distressing, increase depression and contribute to social withdrawal.

Aims
To systematically assess the occurrence of voice content regarding appearance and identify correlates.

Method
Sixty patients experiencing verbal auditory hallucinations at least once a week in the context of non-affective psychosis completed a measure assessing positive and negative voice content about appearance. They also completed assessments about body image, self-esteem, psychiatric symptoms and well-being.

Results
Fifty-five (91.7%) participants reported hearing voices comment on their appearance. A total of 54 (90%) patients reported negative voice content about their appearance with 30 (50%) patients experienced negative appearance comments on a daily basis. The most common negative comment was ‘the voices tell me that I am ugly’ (n = 48, 80%). There were 39 (65%) patients who reported positive voice content on appearance. The most frequent positive comment was ‘I look as nice as other people’ (n = 26, 43.3%). Negative voice content about appearance was associated with body image concerns, paranoia, voice hearing severity, depression, worry, negative self-beliefs and safety-seeking behaviours. Positive appearance voice content was associated with greater body esteem and well-being and lower levels of depression and insomnia.

Conclusions
Voice content about appearance is very common for patients seen in clinical services. Negative voice content may reflect – and subsequently reinforce – negative beliefs about one's appearance, low self-esteem, worry and paranoia.

Declaration of interest
None.
Machine-Learning and Stochastic Tumor Growth Models for Predicting Outcomes in Patients With Advanced Non–Small-Cell Lung Cancer
Authors: Siah Kien Wei , Khozin Sean , Wong Chi Heem , Lo Andrew W. 
Published: September 2019

PURPOSEThe prediction of clinical outcomes for patients with cancer is central to precision medicine and the design of clinical trials. We developed and validated machine-learning models for three important clinical end points in patients with advanced non–small-cell lung cancer (NSCLC)—objective response (OR), progression-free survival (PFS), and overall survival (OS)—using routinely collected patient and disease variables.METHODSWe aggregated patient-level data from 17 randomized clinical trials recently submitted to the US Food and Drug Administration evaluating molecularly targeted therapy and immunotherapy in patients with advanced NSCLC. To our knowledge, this is one of the largest studies of NSCLC to consider biomarker and inhibitor therapy as candidate predictive variables. We developed a stochastic tumor growth model to predict tumor response and explored the performance of a range of machine-learning algorithms and survival models. Models were evaluated on out-of-sample data using the standard area under the receiver operating characteristic curve and concordance index (C-index) performance metrics.RESULTSOur models achieved promising out-of-sample predictive performances of 0.79 area under the receiver operating characteristic curve (95% CI, 0.77 to 0.81), 0.67 C-index (95% CI, 0.66 to 0.69), and 0.73 C-index (95% CI, 0.72 to 0.74) for OR, PFS, and OS, respectively. The calibration plots for PFS and OS suggested good agreement between actual and predicted survival probabilities. In addition, the Kaplan-Meier survival curves showed that the difference in survival between the low- and high-risk groups was significant (log-rank test P < .001) for both PFS and OS.CONCLUSIONBiomarker status was the strongest predictor of OR, PFS, and OS in patients with advanced NSCLC treated with immune checkpoint inhibitors and targeted therapies. However, single biomarkers have limited predictive value, especially for programmed death-ligand 1 immunotherapy. To advance beyond the results achieved in this study, more comprehensive data on composite multiomic signatures is required.
Distinct functions and temporal regulation of methylated histone H3 during early embryogenesis
Authors: Mutlu Beste , Chen Huei-Mei , Gutnik Silvia , Hall David H. , Keppler-Ross Sabine , Mango Susan E. 
Published: September 2019

ABSTRACT
During the first hours of embryogenesis, formation of higher-order heterochromatin coincides with the loss of developmental potential. Here, we examine the relationship between these two events, and we probe the processes that contribute to the timing of their onset. Mutations that disrupt histone H3 lysine 9 (H3K9) methyltransferases reveal that the methyltransferase MET-2 helps terminate developmental plasticity, through mono- and di-methylation of H3K9 (me1/me2), and promotes heterochromatin formation, through H3K9me3. Although loss of H3K9me3 perturbs formation of higher-order heterochromatin, embryos are still able to terminate plasticity, indicating that the two processes can be uncoupled. Methylated H3K9 appears gradually in developing C. elegans embryos and depends on nuclear localization of MET-2. We find that the timing of H3K9me2 and nuclear MET-2 is sensitive to rapid cell cycles, but not to zygotic genome activation or cell counting. These data reveal distinct roles for different H3K9 methylation states in the generation of heterochromatin and loss of developmental plasticity by MET-2, and identify the cell cycle as a crucial parameter of MET-2 regulation.
The control of gene expression and cell identity by H3K9 trimethylation
Authors: Ninova Maria , Fejes Tóth Katalin , Aravin Alexei A. 
Published: September 2019

ABSTRACT
Histone 3 lysine 9 trimethylation (H3K9me3) is a conserved histone modification that is best known for its role in constitutive heterochromatin formation and the repression of repetitive DNA elements. More recently, it has become evident that H3K9me3 is also deposited at certain loci in a tissue-specific manner and plays important roles in regulating cell identity. Notably, H3K9me3 can repress genes encoding silencing factors, pointing to a fundamental principle of repressive chromatin auto-regulation. Interestingly, recent studies have shown that H3K9me3 deposition requires protein SUMOylation in different contexts, suggesting that the SUMO pathway functions as an important module in gene silencing and heterochromatin formation. In this Review, we discuss the role of H3K9me3 in gene regulation in various systems and the molecular mechanisms that guide the silencing machinery to target loci.
RadiationGeneSigDB: a database of oxic and hypoxic radiation response gene signatures and their utility in pre-clinical research
Authors: Manem Venkata SK , Dhawan Andrew 
Published: September 2019

Objective: Radiation therapy is among the most effective and widely used modalities of cancer therapy in current clinical practice. In this era of personalized radiation medicine, high-throughput data now provide the means to investigate novel biomarkers of radiation response. Large-scale efforts have identified several radiation response signatures, which poses two challenges, namely, their analytical validity and redundancy of gene signatures. Methods: To address these fundamental radiogenomics questions, we curated a database of gene expression signatures predictive of radiation response under oxic and hypoxic conditions. RadiationGeneSigDB has a collection of 11 oxic and 24 hypoxic signatures with the standardized gene list as a gene symbol, Entrez gene ID, and its function. We present the utility of this database by gaining an understanding of hypoxia-associated miRNA by applying a penalized multivariate model; by comparing breast cancer oxic signatures in cell line data vs patient data; and by comparing the similarity of head and neck cancer hypoxia signatures at the pathway level in clinical tumour data. Results: We obtained a set of miRNA highly associated both positively and negatively to the hypoxia gene signatures, across pan-cancer. In addition, we identified moderate correlations between breast cancer oxic signatures in patient data, and significant differences across molecular subtypes. Moreover, we also found that different set of pathways to be enriched using the head and neck hypoxia signatures, although, they are found to be concordant when applied on the patient data. Conclusion: This valuable, curated repertoire of published gene expression signatures provides motivating case studies for how to search for similarities in radiation response for tumours arising from different tissues across model systems under oxic and hypoxic conditions, and how a well-curated set of gene signatures can be used to generate novel biological hypotheses about the functions of non-coding RNA. Advances in knowledge: We envision that RadiationSigDB database will help accelerate preclinical radiotherapeutic discovery pipelines in terms of analytical validity of novel biomarkers of radiation response and the need for ensemble approaches to clinical genomic biomarkers.
NHS hospital readiness to embrace the proposed NICE guidelines on abdominal aortic aneurysm: a public perspective
Authors: Misro A , Kanagalingam D , Theivacumar S 
Published: September 2019

Introduction The National Institute for Health and Care Excellence published a draft consultation update on abdominal aortic aneurysm, which was expected to be published on 7 November 2018. This article analyses the readiness of NHS hospitals and their workforce to embrace the proposed guidelines. Methods The trust and individual surgeon-level anonymised data in the public domain for elective, rupture and complex abdominal aortic aneurysm cases were collected and analysed for all the acute care trusts providing these services from the Vascular Society of Great Briton and Ireland’s prospective National Vascular Registry database. Results Of the 95 acute care trusts providing the service for the year 2017, the annual volume of infrarenal abdominal aortic aneurysm (both endovascular and open repairs) ranged between 0 and 137. Of these, 64 (67.36%) trusts had an annual volume of fewer than 60 cases. A total of 366 (approximately 75% of 490) vascular surgeons have performed 10 or fewer open abdominal aortic aneurysm repairs in three years (2014–2016) with a mean operating volume of 1.452 procedures per surgeon per three years (n = 254, median 0, interquartile range, IQR, 0–3, 0.484 procedures per surgeon per year) and about 51% of the vascular surgeons have only performed five or fewer procedures in those three years with a mean operating volume of 3.455 per surgeon per three years (n = 367, median 3, IQR 0–3, 1.151 per surgeon per year). Conclusion The observations show that most UK acute hospitals lack the optimum case volume necessary to embrace the proposed change in the guideline.
Sex determination in Northern Thai from crania by using computer-aided design software and conventional caliper methods
Authors: Thuanthong Toonlanat , Sudwan Paiwan 
Published: September 2019

Abstract

Background
Identification of sex from skeletal remains is an essential step in forensic anthropology. The skull is the second choice, after the pelvis, to estimate sex by osteometric methods.

Objective
To evaluate the process of identification of sex in Northern Thai from crania by using computer-aided design (AutoCAD) software and conventional caliper methods.

Methods
Dry skulls of 86 men and 74 women were examined. AutoCAD software and digital calipers were used to measure dimensions. Eleven of the 15 parameters were created for this study.

Results
Men are significantly larger than women in all parameters, except in the nasospinale–prosthion measurement. There were no significant differences in the intraobserver error test and between the AutoCAD and digital caliper measurements. The logistic regression analysis yielded a sex classification accuracy rate of 92.9% in men, 93.4% in women, and 93.1% of overall accuracy for AutoCAD software. When using digital calipers, there was an accuracy rate of 89.3% in men, 94.7% in women, and 91.9% for overall accuracy.

Conclusions
AutoCAD software is a reliable method to predict the sex and provide high accuracy in sex determination from crania.
The integral polytope group
Authors: Funke Florian 
Published: September 2019

AbstractWe show that the Grothendieck group associated to integral polytopes in ℝnis free-abelian, by providing an explicit basis. Moreover, we identify the involution on this polytope group given by reflection about the origin as a sum of Euler characteristic type. We also compute the kernel of the norm map sending a polytope to its induced seminorm on the dual of ℝn.
Blocking Coalitions and Fairness in Asset Markets and Asymmetric Information Economies
Authors: Bhowmik Anuj , Gabriella Graziano Maria 
Published: September 2019

Abstract
This paper analyses two properties of the core in a two-period exchange economy under uncertainty: the veto power of arbitrary sized coalitions; and coalitional fairness of core allocations. We study these properties in relation to classical (static) and sequential (dynamic) core notions and apply our results to asset markets and asymmetric information models. We develop a formal setting where consumption sets have no lower bound and impose a series of general restrictions on the first period trades of each agent. All our results are applications of the same lemma about improvements to an allocation that is either non-core or non-coalitionally fair. Roughly speaking, the lemma states that if all the members of a coalition achieve a better allocation in some way (for instance, by blocking the status quo allocation or because they envy the net trade of other coalitions) then an alternative improvement can be obtained through a perturbation of the initial improvement.
Deep Learning for Prediction of Diaphragm Activity from the Surface Electromyogram
Authors: Bockelmann Niclas , Graßhoff Jan , Hansen Lasse , Bellani Giacomo , Heinrich Mattias P. , Rostalski Philipp 
Published: September 2019

Abstract
The electrical activity of the diaphragm (EAdi) is a novel monitoring parameter for patients under assisted ventilation and is used for assessing the patient’s neural respiratory drive. It is recorded by an array of electrodes placed inside the esophagus at the level of the diaphragm. A noninvasive alternative is the measurement of the electromyogram by means of skin surface electrodes (sEMG). The respiratory sEMG signal, however, is subject to electrocardiographic interference and crosstalk from other muscles and may also pick up a different part of the muscular activity. In this work, we propose to use a deep neural network to predict the electrical activity of the diaphragm as measured by a nasogastric catheter from sEMG measurements. We use a ResNet based architecture and train the network to directly regress the EAdi as a supervised learning task - we further investigate a heatmap based regression approach. The proposed methods are evaluated on a clinical dataset consisting of 77 recordings from mechanically ventilated patients. For the direct regression task, the network’s predictions reach a Pearson correlation coefficient (PCC) of 0.818 with EAdi on the hold-out set. The heatmap regression increases the PCC to 0.830 while at the same time achieving a lower mean absolute error, indicating a superior performance. From our results we conclude that sEMG measurements may be used to predict the internal activity of the diaphragm as measured invasively using a nasogastric catheter.
A computer-assisted optimization approach for orthognathic surgery planning
Authors: Weichel Frederic , Eisenmann Urs , Richter Sarah , Hagen Niclas , Rückschloß Thomas , Freudlsperger Christian , Dickhaus Hartmut 
Published: September 2019

Abstract
Orthognathic surgery is used to treat misaligned jaws in adults by repositioning them. Intervention planning has to take into account different clinical, anatomical, functional, and aesthetic parameters to determine the optimal position. Current planning systems usually present 3D surface models obtained from a CT or Cone-Beam scan of the patient. The surgeon then interactively positions the upper and lower jaw. Thus, the surgeon can manually optimize anatomical aspects but has to consider functional and aesthetic effects simultaneously, which may be error-prone. We are developing a computer-assisted planning system which generates an optimized position for both jaws based on different analyses (cephalometric, plaster model, photostat) of the head, using a gradient descent algorithm. For this purpose, landmarks are interactively identified on a 3D surface representation. The system is developed as a plugin for MITK utilizing a knowledge base realized in the sematic web standard RDFS, which is queried with SPARQL requests. In a preliminary evaluation with five different cases we compare the automatically generated planning proposal with the planning results of a maxillofacial expert (ground truth). Good general agreement is observed, although more research for the identification and development of 3D cephalometric analyses is needed.
Self-adapting Classification System for Swallow Intention Detection in Dysphagia Therapy
Authors: Riebold Benjamin , Nahrstaedt Holger , Schauer Thomas , Seidl Rainer O. 
Published: September 2019

Abstract
In dysphagia the ability of elevating the larynx and hyoid is usually impaired. Electromyography (EMG) and Bioimpedance (BI) measurements at the neck can be used to trigger functional electrical stimulation (FES) of swallowing related muscles. The height and speed of larynx elevation can be assessed by evaluating the BI during a swallow. For the triggering of an supporting FES and for biofeedback online detection of swallow onsets is required. Patients can practice by a gamified biofeedback to swallow harder, swallow in a timely manner or to maintain the larynx elevation for a longer time period (Mendelson maneuver). The success of the stimulation and biofeedback therapy as well as the acceptance by the patient strongly depends on the precise detection of swallow onsets. We have introduced a classification algorithm based on a random forest classifier to trigger FES in phase with voluntary swallowing based on EMG and BI. Although the classification is successful in healthy subjects, difficulties appear in the utilization on some patients. The reason for this can be found in a strongly varying residual swallow activity. Usually the activity of EMG and change in BI are smaller in patients compared to healthy subjects. Thus an adaption procedure is needed, that can be easily applied. In this paper we introduce an algorithm that is capable to find an optimal classifier for a patient in terms of sensitivity. The adaption algorithm uses a small number of recorded swallow onsets of a patient at the beginning of a therapy session to evaluate different classifiers and to pick the most suitable for the treatment. The set of random forest classifiers has been trained with data from healthy subjects by step wise shifting the class weights of swallows and non-swallows, yielding classifiers with different sensitivities. The evaluation is done using data from 41 patients. It showed that the sensitivity of the classification can be increased by 4 to 6 % in average compared to fixed classifiers, but up to 66 % for individual patients. Finally, we studied the effect this adaptive classifier in triggered stimulation therapy in a single dysphagia patient. Swallowing performance was measurements during one week of therapy consisting of eleven therapy session. An improvement of 40 and 63 % in larynx elevation and speed could be observed, respectively.
HRV (Heart Rate Variability) as a non-invasive measurement method for performance diagnostics and training control
Authors: Scherer Matthias , Martinek Johannes , Mayr Winfried 
Published: September 2019

Abstract
The aim of this study was to determine whether non-invasive heart rate variability (HRV) recordings can be used to monitor training exercises and to estimate athletic performance. Thus far, condition and performance have been evaluated with lactate test procedures and spirometry. Several tests were conducted to determine the relationship of data from lactate test samplings, spirometry and HRV recordings. Four groups of professional athletes in different disciplines such as ball sports (n=15), martial arts (n=17), endurance sports (n=8) and hobby athletes (n=6) underwent a standardized treadmill or bicycle ergometer step test while increasing load rates, e.g. 2 km/h or 20-50 Watt every 3.5 minutes, synchronized with standardized series of lactate test sampling, spirometry and ECG recording. An inclusion criterion for all athlete groups was a minimum training frequency of an hour, five days a week focusing on continuous performance improvement. Evidence shows that offline analysis of ECG data allows conclusions on actual individual athletic performance without the need for complex instrumentation and laboratory environment. The total power parameter of the HRV reaches a plateau phase in all tested subjects and this plateau phase reaches zero near the 2 mmol threshold of lactate concentration in all subjects recorded on a bicycle ergometer. Nine out of ten subjects measured on the bicycle ergometer had negatively correlating data of lactate concentration and total power of HRV (α < 0.05). Lactate measurements using treadmills require resting periods for blood sampling. As the HRV increases instantly in these resting periods, the use of bicycle ergometers, where no testing breaks are needed, is recommended for further research.