bluuebunny/crossref_metadata_2025_split huggingface dataset:
Descriptive analysis of effect of uptake of comprehensive antenatal care services on neonatal mortality, Kenya
Authors: Adi Galgallo Dahabo , Gura Roka Zeinab , Boru Waqo G , Ransom James 
Published: September 2019

Background Antenatal care services help decrease neonatal mortality. Laboratory profiling is a highly recommended part of antenatal care services, but it is often neglected. Aims To explore the importance of comprehensive antenatal care services in reducing neonatal mortality among births at Moyale Sub-County Referral Hospital in Kenya. Methods A retrospective review was conducted of maternity records of all women aged 15 years old or more who gave birth at Moyale Sub-County Referral Hospital between June 2014 and May 2015. Stillbirths were excluded from the analysis. Data were entered into Microsoft Excel and descriptive statistics calculated. A total of 1062 women were included in the study, with mean age of 24 ± 9.1 years. Of these, 11% had no antenatal care visits, 2% were HIV-positive, and all lived within 10 km of Moyale Sub-County Referral Hospital. Findings Children of women who had no antenatal care visits were 2.7 times more likely to die within 28 days of birth compared to children born to women who had 1 antenatal care visit, and 8.5 times more likely to die compared to women who had at least three antenatal care visits. Conclusions Antenatal care profiling helps reduce neonatal mortality by capturing early diagnosis of preventable conditions that affect birth outcomes.
Evaluation of SHP1-P2 methylation as a biomarker of lymph node metastasis in patients with squamous cell carcinoma of the head and neck
Authors: Kitkumthorn Nakarin , Keelawat Somboon , Wongphoom Jutamas , Rattanatanyong Prakasit , Mutirangura Apiwat 
Published: September 2019

Abstract

Background
Hypermethylation of Src homology region 2 domain-containing protein-tyrosine phosphatase 1 promoter 2 (SHP1-P2) has been proven as an epithelial-specific marker. This marker has been used for the detection of lymph node metastasis in patients with lung cancer or colon cancer.

Objectives
To investigate SHP1-P2 methylation in patients with squamous cell carcinoma of the head and neck (HNSCC) and determine its potential for micrometastasis detection in the lymph nodes of patients with HNSCC.

Methods

SHP1-P2 methylation levels were analyzed by combined methylation-specific primer TaqMan real-time PCR in 5 sample groups: normal tonsils (n = 10), microdissected squamous cell carcinoma epithelia (n = 9), nonmetastatic head and neck cancer lymph nodes (LN N0, n = 15), metastatic HNSCC histologically negative for tumor cells (LN–, n = 18), and matched cases histologically positive for tumor cells (LN+, n = 18).

Results

SHP1-P2 methylation of 10.27 ± 4.05% was found in normal tonsils as a lymphoid tissue baseline, whereas it was 61.31 ± 17.00% in microdissected cancer cell controls. In the 3 lymph node groups, the SHP1-P2 methylation levels were 9.99 ± 6.61% for LN N0, 14.49 ± 10.03% for LN- Nx, and 41.01 ± 24.51% for LN+ Nx. The methylation levels for LN- Nx and LN+ Nx were significantly different (P
= 0.0002). Receiver operating characteristic curve analysis of SHP1-P2 methylation demonstrated an area under the curve of 0.637 in distinguishing LN N0 from LN– Nx.

Conclusions

SHP1-P2 methylation was high in HNSCC, and low in lymphoid tissues. This methylation difference is concordant with lymph node metastasis.
Anatomic variations of coronary arteries: origins, branching patterns, and abnormalities
Authors: Khwansang Natatcha , Chentanez Vilai 
Published: September 2019

Abstract

Background
Anatomic variations in orifices, courses, branching patterns, and abnormalities of coronary arteries could affect blood supply, hemodynamic characteristics, and clinical symptoms, and could be a risk of atherosclerosis.

Objectives
To investigate the location and number of both coronary orifices in the aortic cusps, branching patterns of left main trunk, dominant pattern of posterior interventricular artery (PIA), prevalence of right posterior diagonal artery (RPDA), myocardial bridge, and other abnormalities.

Methods
We dissected 95 heart specimens from cadavers of Thai donors without the history of surgery, and the dominant patterns, location and number of orifices in the aortic cusps, branching patterns, origin and number of conal arteries, and occurrence of RPDA were determined.

Results
Dual aortic origin of the coronary orifice was the most common condition. Anomalous 2 orifices in the left aortic cusp were found in one specimen in which the right coronary artery (RCA) arose from aortic cusp and had an interarterial course. Right dominance and trifurcated form of left main trunk were found more frequently. Most frequently 2 conal arteries were found. RPDA was found in 45% and mostly originated from RCA. The prevalence of myocardial bridge was 62% and located mostly on the anterior interventricular artery (AIA).

Conclusions
The prevalence of right dominance, RPDA, the atypical origin of RCA from the left sinus, and the prevalence of myocardial bridges was more frequent than reported by others, whereas the dual aortic origin from both cusps and the prevalence of bifurcated left main trunk was less frequent.
Deep Reinforcement Learning for the Navigation of Neurovascular Catheters
Authors: Behr Tobias , Pusch Tim Philipp , Siegfarth Marius , Hüsener Dominik , Mörschel Tobias , Karstensen Lennart 
Published: September 2019

Abstract
Endovascular catheters are necessary for state-ofthe- art treatments of life-threatening and time-critical diseases like strokes and heart attacks. Navigating them through the vascular tree is a highly challenging task. We present our preliminary results for the autonomous control of a guidewire through a vessel phantom with the help of Deep Reinforcement Learning. We trained Deep-Q-Network (DQN) and Deep Deterministic Policy Gradient (DDPG) agents on a simulated vessel phantom and evaluated the training performance. We also investigated the effect of the two enhancements Hindsight Experience Replay (HER) and Human Demonstration (HD) on the training speed of our agents. The results show that the agents are capable of learning to navigate a guidewire from a random start point in the vessel phantom to a random goal. This is achieved with an average success rate of 86.5% for DQN and 89.6% for DDPG. The use of HER and HD significantly increases the training speed. The results are promising and future research should address more complex vessel phantoms and the use of a combination of guidewire and catheter.
Intraoperative Registration of 2D C-arm Images with Preoperative CT Data in Computer Assisted Spine Surgery: Motivation to Use Convolutional Neural Networks for Initial Pose Generator
Authors: Alvarez-Gomez Julio , Roth Hubert , Wahrburg Jürgen 
Published: September 2019

Abstract
In this paper, we present an approach for getting an initial pose to use in a 2D/3D registration process for computer-assisted spine surgery. This is an iterative process that requires an initial pose close to the actual final pose. When using a proper initial pose, we get registrations within two millimeters of accuracy. Consequently, we developed a fully connected neural network (FCNN), which predicts the pose of a specific 2D image within an acceptable range. Therefore, we can use this result as the initial pose for the registration process. However, the inability of the FCNN for learning spatial attributes, and the decrease of the resolution of the images before inserting them in the FCNN, make the variance of the prediction large enough to make some of the predictions entirely out of the acceptable range. Additionally, new researches in deep learning field have shown that convolutional neural networks (CNNs) offer high advantages when the inputs of the net are images. We consider that using CNNs can help to improve our results, generalizing the system for a greater variety of inputs, and facilitating the integration with our current workflow. Then we present an outline for a CNN for our application, and some further steps we need to complete to achieve this implementation.
Surface modification of Polydimethylsiloxane by hydrogels for microfluidic applications
Authors: Kemkemer Ralf , Zenghao Zhang , Linxiao Yang , Athanasopulu Kiriaki , Frey Kerstin , Cui Zhishan , Su Haijia , Luo Liu 
Published: September 2019

Abstract
In vitro, hydrogel-based ECMs for functionalizing surfaces of various material have played an essential role in mimicking native tissue matrix. Polydimethylsiloxane (PDMS) is widely used to build microfluidic or organ-on-chip devices compatible with cells due to its easy handling in cast replication. Despite such advantages, the limitation of PDMS is its hydrophobic surface property. To improve wettability of PDMS-based devices, alginate, a naturally derived polysaccharide, was covalently bound to the PDMS surface. This alginate then crosslinked further hydrogel onto the PDMS surface in desired layer thickness. Hydrogel-modified PDMS was used for coating a topography chip system and in vitro investigation of cell growth on the surfaces. Moreover, such hydrophilic hydrogel-coated PDMS is utilized in a microfluidic device to prevent unspecific absorption of organic solutions. Hence, in both exemplary studies, PDMS surface properties were modified leading to improved devices.
Camera-based spatial assessment of perfusion upon stimuli
Authors: Fleischhauer Vincent , Ruprecht Nora , Zaunseder Sebastian 
Published: September 2019

Abstract
Imaging photoplethysmography allows to capture spatio-temporal patterns related to the perfusion. One such approach is based on the analysis of the time delay between pulse waves at different locations by so-called phase maps. There are different ways to establish such maps. However, neither a comparison between existing methods has been published nor has the impact of different stimuli been sufficiently examined until today. In this work, we compare three previously published approaches for the generation of phase maps and investigate the impact of two physiological stimuli on such maps. Our results show pairwise correlation coefficients between the different approaches of phase map generation from r = 0.65 to r = 0.82, indicating substantial differences between maps. The different maps reflect our physiological expectation in varying degrees. Particularly for a weaker (distant) stimulation refinements are needed to reveal characteristic changes.
Medical device innovations for cardiovascular, ophthalmologic and otolaryngologic applications
Authors: Grabow Niels , Senz Volkmar , Schmitz Klaus-Peter 
Published: September 2019

Abstract
The consortium RESPONSE is a cooperation between partners from science and industry within the BMBF-Program “Twenty20 - Partnership for Innovation”, 2014-2021. RESPONSE gives its partners opportunities to put medical device innovations into practice more efficiently. In order to accelerate innovation processes, joint efforts are being made along the entire translation chain. RESPONSE is focusing on the development of novel concepts of implantable medical devices for cardiovascular, ophthalmologic and ENT application. Platform technology approaches are being used to extend the range of device applications. See also: www.response.uni-rostock.de
Tissue biomimicry using cross-linked electrospun nonwoven fibre composites
Authors: Illner Sabine , Arbeiter Daniela , Teske Michael , Khaimov Valeria , Oschatz Stefan , Senz Volkmar , Grabow Niels , Kohse Stefanie , Schmitz Klaus-Peter 
Published: September 2019

Abstract
Mimicking the structural properties of natural tissue was aimed to be achieved by combining complementary mechanical properties of materials showing high tensile strength with those of high elasticity. By using two polymers with different properties, the advantages of both can be combined to access innovative materials for biomedical applications. Dual co-electrospinning was established to generate biocompatible nonwoven fibre composites with fused properties from polyamide (PA6) and polyurethane based silicone elastomers (PU-co-Si), respectively. By electrospinning both compounds simultaneously, significant advantages, such as combining different fibre thicknesses and mechanical properties, are accessible. Furthermore, the effect on the fibres via an optional post-processing step in the shape of different thermal treatments was investigated. Initial results concerning surface morphology, biocompatibility and tensile properties of the obtained electrospun nonwovens are very auspicious. Thus, the suitability of two complementary polymer classes for tissue biomimicry through a synthetic approach was shown, offering the opportunity of novel implant materials for permanent replacement of biological tissue.
Implantomics: A Paradigm Shift in Implantology
Authors: Jennissen H. P. 
Published: September 2019

Abstract
Implantomics is the science of the implantome. The implantome is a blend of the two terms implant and proteome. The proteome is defined as the protein complement of the genome. The term proteome also implies the mass screening of proteins for the determination of all proteins - and indirectly of all genes - involved in a certain tissue or organ response. In this sense the term proteome is employed here in a new way to specify the totality of proteins associated with a foreign body inserted into the human body. It will be addressed, why the determination of the implanttome is important and which role the implantome may play in the bone-implant interface.
Industrial robots for teleoperated surgery – a systematic review of existing approaches
Authors: Schäfer Max B. , Stewart Kent W. , Pott Peter P. 
Published: September 2019

Abstract
Robotic assistance in surgical interventions has been shown to improve both the surgical outcome and the surgeon’s performance. However, cost-efficient implementation of such systems in an operating room workflow is not yet resolved. Most of the current approaches use highly specialized and purpose-built robotic components, resulting in large costs. This paper presents an investigation into the usage of off-the-shelf robots as cost-efficient basis for teleoperated surgery. In addition, the modifications required of the robot and/or operating environment to make it suitable for the medical setting are assessed. The considered systems are found via a literature search and the MERODA-database, specifically focusing on systems designed for teleoperated surgery which use industrial robots. Among the 126 telemanipulated systems found, only 10 use industrial robots for surgical procedures. Overall, due to the better availability, reduced costs, and increased performance, current industrial robots should be further considered for new and versatile lowcost approaches to teleoperated surgery.
Towards automated and painless venipuncture – vibratory needle insertion techniques
Authors: Liu Jan , Stewart Kent W. , Pott Peter P. 
Published: September 2019

Abstract
The insertion of a needle into soft inhomogeneous tissue is required for many medical procedures. It has been shown that vibratory needle insertion methods have the ability to reduce insertion forces, which are correlated with increased needle placement precision, and reduced frequency and intensity of pain and trauma felt. This paper reviews different vibratory needle insertion methods that have been studied experimentally, addressing vibration generation, vibration frequency and amplitude, and force measurement. Reductions of up to 73 % in peak insertion force (150 Hz), and 37 % in placement error (15 Hz) were reported. Additionally, ultrasonic vibration (84 kHz) reduced the force by up to 28 %. The results of vibratory insertion show promise, specifically in regard to automated needle devices.
Cytotoxicity of Catalysed Silicone Resin Coatings for Smart Biomedical Devices
Authors: Werner Valerie M. K. , Kist Arian , Eblenkamp Markus 
Published: September 2019

Abstract
Equipping medical devices with smart technologies holds great potential for the development of modern medical products. The development requires the identification of new integration strategies and the research of new material combinations due to the miniaturization of systems and increasing production figures. The realization of Smart Biomedical Devices requires a sufficient barrier effect (bioprotection) by appropriate encapsulation of the electronic components. Thinnest polymer coatings have proven to be suitable for conformal encapsulation. The aim of the study was to investigate the fundamental suitability of thin-film lacquers added with catalysts as coating materials for electronic systems with regard to their biological use. Due to long curing times of up to 14 days, eight different catalysts based on different chemical structures were added to the coating materials and their influence on a cytotoxic effect was investigated. A non-cytotoxic effect was observed for the organometallic catalysts based on tin, zirconium, titanium, bismuth, and tertiary amine. Most were resistant to steam sterilization. The curing time of the non-cytotoxic coatings could be significantly reduced by the addition of catalysts. The shortening of process times is an important economic aspect in the production of mass-produced Smart Biomedical Devices.
Automatic Orientation Estimation of Inertial Sensors in C-Arm CT Projections
Authors: Thies Mareike , Maier Jennifer , Eskofier Björn , Maier Andreas , Levenston Marc , Gold Garry , Fahrig Rebecca 
Published: September 2019

Abstract
To obtain CT images of the knee joint in a more lifelike position, data acquisition can be performed with patients in standing rather than in lying position. However, in that situation, people tend to show involuntary motion. One possibility to compensate for that motion is the use of Inertial Measurement Units, that capture the accelerations during the scan. For this purpose, their local coordinate system needs to be known. An estimation based on the SIFT algorithm was implemented and compared to an existing approach that uses the Fast Radial Symmetry transform and to expert labels for evaluation. The SIFT method showed to be superior to the existing approach as it could extract stable feature points from the projections that were used to estimate the three-dimensional coordinate system in a reliable manner. The final algorithm achieved a mean euclidean distance of 2.61 mm between the calculated position of the origin and the assumed ground truth by the expert labels.
Dynamic image analysis of transparent particles released during the simulated use test of cardiovascular devices
Authors: Kurzhals Anja , Brandt-Wunderlich Christoph , Grabow Niels , Schmidt Wolfram , Schmitz Klaus-Peter 
Published: September 2019

Abstract
For product approval of coated cardiovascular devices, the assessment of particle release is essential. Particularly challenging are delivery systems equipped with hydrophilic coatings releasing highly transparent particles. The aim of this study was to compare two different methods of particle counting, namely the light obscuration method and the dynamic image analysis (DIA), with respect to optical transparent particles. The particles were collected during the simulated use of cardiovascular catheters and analysed in suspension with a dynamic imaging device (FlowCam, Fluid Imaging Technologies). Particles were detected by a greyscale threshold and imaged to analyse their shape and transparency. The statistical influence of the threshold on particle counts and size distribution was determined and compared to light obscuration particle counting (Model 9703 with sensor HRLD 400CE, HIAC ROYCO). The light obscuration method provided lower particle counts in suspensions containing a high amount of transparent particles. The lower the detection threshold, the higher the particle counts were. In conclusion, it is important to adapt the threshold value for samples that are expected to contain a high amount of transparent particles. DIA may be suggested as a valuable additional method for particulate analysis.
Construction of a novel microfluidic experimental setup for testing recent glaucoma drainage devices
Authors: Kara Emre , İhsan Kutlar Ahmet , Güngör Kıvanç 
Published: September 2019

Abstract
Glaucoma is an eye disorder in which the optic nerve is damaged over time due to a sustained elevation of the intraocular pressure (IOP). Being the second leading cause of blindness according to the reports of the World Health Organization, glaucoma is not only a serious ocular disease that threatens individuals, but also a community health problem. In recent years, great improvement has been achieved in the technology of implants used in the treatment of the disease. Despite the great effort dedicated to the design and implementation of the glaucoma drainage devices (GDD), they still have unsolved problems and weaknesses. Most of the currently employed GDDs are very simple and have major problems such as reversed flow, choking and a coarse interval of pressure control. Experiments must be devised to investigate the flow behavior inside these devices. In this study, an accurate microfluidics experimental setup is constructed to analyze and characterize the in-vitro performance of actively employed GDDs on the glaucoma treatment. Proposed setup includes a pressurized fluid reservoir, ELVEFLOW microfluidics flow rate measurement/control unit, microfluidics flow/pressure sensors, and data analysis system. In the setup, more precise measurements than experimental setups in literature is planned to be provided. It is estimated that the results showing consistency with in-vivo measurements will be obtained, behavior of the fluid passing through the GDDs will be observed and issues with design flaws will be addressed.
Quantifying the uncertainty of deep learning-based computer-aided diagnosis for patient safety
Authors: Laves Max-Heinrich , Ihler Sontje , Ortmaier Tobias , Kahrs Lüder A. 
Published: September 2019

Abstract
In this work, we discuss epistemic uncertainty estimation obtained by Bayesian inference in diagnostic classifiers and show that the prediction uncertainty highly correlates with goodness of prediction. We train the ResNet-18 image classifier on a dataset of 84,484 optical coherence tomography scans showing four different retinal conditions. Dropout is added before every building block of ResNet, creating an approximation to a Bayesian classifier. Monte Carlo sampling is applied with dropout at test time for uncertainty estimation. In Monte Carlo experiments, multiple forward passes are performed to get a distribution of the class labels. The variance and the entropy of the distribution is used as metrics for uncertainty. Our results show strong correlation with ρ = 0.99 between prediction uncertainty and prediction error. Mean uncertainty of incorrectly diagnosed cases was significantly higher than mean uncertainty of correctly diagnosed cases. Modeling of the prediction uncertainty in computer-aided diagnosis with deep learning yields more reliable results and is therefore expected to increase patient safety. This will help to transfer such systems into clinical routine and to increase the acceptance of machine learning in diagnosis from the standpoint of physicians and patients.