bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of Glenosphere and baseplate parameters on Glenoid bone strains in reverse shoulder Arthroplasty
Authors: Pauzenberger Leo , Dwyer Cory , Obopilwe Elifho , Nowak Michael D. , Cote Mark , Romeo Anthony A. , Mazzocca Augustus D. , Dyrna Felix 
Published: December 2019

AbstractBackgroundLittle is known about the strains at the glenoid near the bone-implant interface in reverse shoulder arthroplasty. The purpose of the current study was to evaluate the strains on the glenoid bone under a compressive load after implantation of three different sizes of metal-backed baseplates in either inferior or superior position in combination with three different sizes of glenospheres and three different glenosphere designs.MethodsThree sizes of baseplates (small, medium, large) were implanted in thirty-six paired human cadaveric scapulae either inferior, flush with the glenoid neck, or with a 5 mm superior offset. Glenospheres were available in three sizes (36 mm, 39 mm, 42 mm) and designs (standard, 4 mm lateralized, 2.5 mm inferiorized). Specimens were mounted in a servo-hydraulic testing apparatus at a 60° angle between the glenoid and actuator holding the humeral component. Four strain-gauge rosettes were placed around the glenoid rim to measure strains transferred to the scapular bone under a compressive load (750 N) relative to the various baseplate-glenosphere combinations. Following repeated compression, a load-to-failure test was performed.ResultsMean overall registered strains were 161με (range: − 1165 to 2347) at the inferior sensor, −2με (range: − 213 to 90) at the superior sensor, −95με (range: − 381 to 254) at the anterior sensor, and 13με (range: − 298 to 128) at the posterior sensor. Measured bone strains did not show any significant differences across tested baseplate and glenosphere design, size, or positioning combinations (p > 0.05for all sensors). Furthermore, linear regression analysis did not identify any of the evaluated parameters as an independent influential factor for strains (p > 0.05for all sensors). Mean load-at-failure was significantly higher in the group of inferior (3347.0 N ± 704.4 N) compared to superior (2763.8 N ± 927.8 N) positioned baseplates(p = 0.046).ConclusionDifferent baseplate positions, baseplate sizes, glenosphere sizes, and glenosphere design or various combinations of these parameters did not significantly influence the measured bone strains at the glenoid near the bone-implant interface in a contemporary reverse shoulder arthroplasty system.Level of evidenceBasic Science Study, Biomechanical Study.
Natural language processing for populating lung cancer clinical research data
Authors: Wang Liwei , Luo Lei , Wang Yanshan , Wampfler Jason , Yang Ping , Liu Hongfang 
Published: December 2019

Abstract
Background
Lung cancer is the second most common cancer for men and women; the wide adoption of electronic health records (EHRs) offers a potential to accelerate cohort-related epidemiological studies using informatics approaches. Since manual extraction from large volumes of text materials is time consuming and labor intensive, some efforts have emerged to automatically extract information from text for lung cancer patients using natural language processing (NLP), an artificial intelligence technique.

Methods
In this study, using an existing cohort of 2311 lung cancer patients with information about stage, histology, tumor grade, and therapies (chemotherapy, radiotherapy and surgery) manually ascertained, we developed and evaluated an NLP system to extract information on these variables automatically for the same patients from clinical narratives including clinical notes, pathology reports and surgery reports.

Results
Evaluation showed promising results with the recalls for stage, histology, tumor grade, and therapies achieving 89, 98, 78, and 100% respectively and the precisions were 70, 88, 90, and 100% respectively.

Conclusion
This study demonstrated the feasibility and accuracy of automatically extracting pre-defined information from clinical narratives for lung cancer research.
RCorp: a resource for chemical disease semantic extraction in Chinese
Authors: Sun Yueping , Hou Li , Qin Lu , Liu Yan , Li Jiao , Qian Qing 
Published: December 2019

Abstract
Background
To robustly identify synergistic combinations of drugs, high-throughput screenings are desirable. It will be of great help to automatically identify the relations in the published papers with machine learning based tools. To support the chemical disease semantic relation extraction especially for chronic diseases, a chronic disease specific corpus for combination therapy discovery in Chinese (RCorp) is manually annotated.

Methods
In this study, we extracted abstracts from a Chinese medical literature server and followed the annotation framework of the BioCreative CDR corpus, with the guidelines modified to make the combination therapy related relations available. An annotation tool was incorporated to the standard annotation process.

Results
The resulting RCorp consists of 339 Chinese biomedical articles with 2367 annotated chemicals, 2113 diseases, 237 symptoms, 164 chemical-induce-disease relations, 163 chemical-induce-symptom relations, and 805 chemical-treat-disease relations. Each annotation includes both the mention text spans and normalized concept identifiers. The corpus gets an inter-annotator agreement score of 0.883 for chemical entities, 0.791 for disease entities which are measured by F score. And the F score for chemical-treat-disease relations gets 0.788 after unifying the entity mentions.

Conclusions
We extracted and manually annotated a chronic disease specific corpus for combination therapy discovery in Chinese. The result analysis of the corpus proves its quality for the combination therapy related knowledge discovery task. Our annotated corpus would be a useful resource for the modelling of entity recognition and relation extraction tools. In the future, an evaluation based on the corpus will be held.
Applying a deep learning-based sequence labeling approach to detect attributes of medical concepts in clinical text
Authors: Xu Jun , Li Zhiheng , Wei Qiang , Wu Yonghui , Xiang Yang , Lee Hee-Jin , Zhang Yaoyun , Wu Stephen , Xu Hua 
Published: December 2019

Abstract
Background
To detect attributes of medical concepts in clinical text, a traditional method often consists of two steps: named entity recognition of attributes and then relation classification between medical concepts and attributes. Here we present a novel solution, in which attribute detection of given concepts is converted into a sequence labeling problem, thus attribute entity recognition and relation classification are done simultaneously within one step.

Methods
A neural architecture combining bidirectional Long Short-Term Memory networks and Conditional Random fields (Bi-LSTMs-CRF) was adopted to detect various medical concept-attribute pairs in an efficient way. We then compared our deep learning-based sequence labeling approach with traditional two-step systems for three different attribute detection tasks: disease-modifier, medication-signature, and lab test-value.

Results
Our results show that the proposed method achieved higher accuracy than the traditional methods for all three medical concept-attribute detection tasks.

Conclusions
This study demonstrates the efficacy of our sequence labeling approach using Bi-LSTM-CRFs on the attribute detection task, indicating its potential to speed up practical clinical NLP applications.
Type 2 diabetes and healthcare resource utilisation in the Kingdom of Bahrain
Authors: Salman Rabha AbdulAziz , AlSayyad Adel Salman , Ludwig Craig 
Published: December 2019

Abstract
Background
Type 2 diabetes is a growing health challenge in the Kingdom of Bahrain, and the disease exerts significant pressure on the healthcare system. The aim of this study was to assess the annual costs and understand the drivers of those costs in the country.

Methods
A sample of 628 patients diagnosed with type 2 diabetes were randomly selected from primary healthcare diabetes clinics, and the direct medical and indirect costs due to type 2 diabetes were analysed for a one-year period. The study used patients’ medical records, interviews and standardised frequency questionnaires to obtain data on demographic and clinical characteristics, complication status, treatment profile, healthcare resource utilisation and absenteeism due to diabetes. The indirect costs were estimated by using the human capital approach. The direct medical and indirect costs attributable to type 2 diabetes were extrapolated to the type 2 diabetes population in Bahrain.

Results
In 2015, the total direct medical cost of type 2 diabetes was 104.7 million Bahraini dinars (BHD), or 277.9 million US dollars (USD), and the average unit cost per person with type 2 diabetes (1162 BHD, or 3084 USD) was more than three times higher than for a person without the condition (372 BHD, or 987 USD). The healthcare costs for patients with both micro- and macrovascular complications were more than three times higher than for patients without complications. Thus, 9% of the patients consumed 21% of the treatment costs due to complications. Complications often lead to hospital admission, and 20% of the patients consumed almost 60% of the healthcare costs attributable to type 2 diabetes due to hospital admissions. The indirect cost due to absenteeism was 1.23 million BHD (3.26 million USD).

Conclusion
Type 2 diabetes exerts significant pressure on Bahrain’s healthcare system – primarily due to costly diabetes-related complications. It is therefore important to optimise the management and control of type 2 diabetes, thereby reducing the risk of disabling and expensive complications.
Association of glycemic variability with left ventricular diastolic function in type 2 diabetes mellitus
Authors: Yokota Shun , Tanaka Hidekazu , Mochizuki Yasuhide , Soga Fumitaka , Yamashita Kentaro , Tanaka Yusuke , Shono Ayu , Suzuki Makiko , Sumimoto Keiko , Mukai Jun , Suto Makiko , Takada Hiroki , Matsumoto Kensuke , Hirota Yushi , Ogawa Wataru , Hirata Ken-ichi 
Published: December 2019

Abstract
Background
Type 2 diabetes mellitus (T2DM) is a major cause of heart failure (HF) with preserved ejection fraction (HFpEF), usually presenting as left ventricular (LV) diastolic dysfunction. Thus, LV diastolic function should be considered a crucial marker of a preclinical form of DM-related cardiac dysfunction. However, the impact of glycemic variability (GV) on LV diastolic function in such patients remains unclear.

Methods
We studied 100 asymptomatic T2DM patients with preserved LV ejection fraction (LVEF) without coronary artery disease (age: 60 ± 14 years, female: 45%). GV was evaluated as standard deviation of blood glucose level using continuous glucose monitoring system for at least 72 consecutive hours. LV diastolic function was defined as mitral inflow E and mitral e’ annular velocities (E/e’), and > 14 was determined as abnormal.

Results
E/e’ in patients with high GV (≥ 35.9 mg/dL) was significantly higher than that in patients with low GV (11.3 ± 3.9 vs. 9.8 ± 2.8, p = 0.03) despite similar age, gender-distribution, and hemoglobin A1c (HbA1c). Multivariate logistic regression analysis showed that GV ≥ 35.9 mg/dL (odds ratio: 3.67; 95% confidence interval: 1.02–13.22; p < 0.05) was an independently associated factor, as was age, of E/e’ > 14. In sequential logistic models for the associations of LV diastolic dysfunction, one model based on clinical variables including age, gender and hypertension was not improved by addition of HbA1c (p = 0.67) but was improved by addition of high GV (p = 0.04).

Conclusion
Since HFpEF is a syndrome caused by diverse agents, reducing GV may represent a potential new therapeutic strategy for the prevention of the development of HFpEF in T2DM patients.
Assessing the role of the private sector in surveillance for malaria elimination in Haiti and the Dominican Republic: a qualitative study
Authors: Sidibe Abigail , Maglior Alysse , Cueto Carmen , Chen Ingrid , Le Menach Arnaud , Chang Michelle A. , Eisele Thomas P. , Andrinopolous Katherine , Cherubin Joseph , Lemoine Jean Frantz , Bennett Adam 
Published: December 2019

Abstract
Background
Haiti and the Dominican Republic (DR) are targeting malaria elimination by 2022. The private health sector has been relatively unengaged in these efforts, even though most primary health care in Haiti is provided by non-state actors, and many people use traditional medicine. Data on private health sector participation in malaria elimination efforts are lacking, as are data on care-seeking behaviour of patients in the private health sector. This study sought to describe the role of private health sector providers, care-seeking behaviour of individuals at high risk of malaria, and possible means of engaging the private health sector in Hispaniola’s malaria elimination efforts.

Methods
In-depth interviews with 26 key informants (e.g. government officials), 62 private providers, and 63 patients of private providers, as well as 12 focus group discussions (FGDs) with community members, were conducted within seven study sites in Haiti and the DR. FGDs focused on local definitions of the private health sector and identified private providers for interview recruitment, while interviews focused on private health sector participation in malaria elimination activities and treatment-seeking behaviour of febrile individuals.

Results
Interviews revealed that self-medication is the most common first step in the trajectory of care for fevers in both Haiti and the DR. Traditional medicine is more commonly used in Haiti than in the DR, with many patients seeking care from traditional healers before, during, and/or after care in the formal health sector. Private providers were interested in participating in malaria elimination efforts but emphasized the need for ongoing support and training. Key informants agreed that the private health sector needs to be engaged, especially traditional healers in Haiti. The Haitian migrant population was reported to be one of the most at-risk groups by participants from both countries.

Conclusion
Malaria elimination efforts across Hispaniola could be enhanced by engaging traditional healers in Haiti and other private providers with ongoing support and trainings; directing educational messaging to encourage proper treatment-seeking behaviour; and refining cross-border strategies for surveillance of the high-risk migrant population. Increasing distribution of rapid diagnostic tests (RDTs) and bi-therapy to select private health sector facilities, accompanied by adopting regulatory policies, could help increase numbers of reported and correctly treated malaria cases.
Antiplasmodial natural products: an update
Authors: Tajuddeen Nasir , Van Heerden Fanie R. 
Published: December 2019

Abstract
Background
Malaria remains a significant public health challenge in regions of the world where it is endemic. An unprecedented decline in malaria incidences was recorded during the last decade due to the availability of effective control interventions, such as the deployment of artemisinin-based combination therapy and insecticide-treated nets. However, according to the World Health Organization, malaria is staging a comeback, in part due to the development of drug resistance. Therefore, there is an urgent need to discover new anti-malarial drugs. This article reviews the literature on natural products with antiplasmodial activity that was reported between 2010 and 2017.

Methods
Relevant literature was sourced by searching the major scientific databases, including Web of Science, ScienceDirect, Scopus, SciFinder, Pubmed, and Google Scholar, using appropriate keyword combinations.

Results and Discussion
A total of 1524 compounds from 397 relevant references, assayed against at least one strain of Plasmodium, were reported in the period under review. Out of these, 39% were described as new natural products, and 29% of the compounds had IC50 ≤ 3.0 µM against at least one strain of Plasmodium. Several of these compounds have the potential to be developed into viable anti-malarial drugs. Also, some of these compounds could play a role in malaria eradication by targeting gametocytes. However, the research into natural products with potential for blocking the transmission of malaria is still in its infancy stage and needs to be vigorously pursued.
Pesticides and the evolution of the genetic structure of Anopheles coluzzii populations in some localities in Benin (West Africa)
Authors: Fassinou Arsène Jacques Y. H. , Koukpo Come Z. , Ossè Razaki A. , Agossa Fiacre R. , Azondékon Roseric , Sominahouin André , Kpanou Casimir , Sagbohan Hermann , Yovogan Boulais , Akogbéto Martin C. , Sezonlin Michel 
Published: December 2019

AbstractBackgroundChanges in the natural habitats of insect groups are determined the genetic polymorphisms between individuals. The objective of this study was to establish the genetic structure of theAnopheles coluzziipopulations in four localities of Benin.MethodsInsecticide surveys and larval sampling were conducted on 4 study localities, including Cotonou, Ketou, Zagnanado, and Sô-Ava. Molecular characterizations were performed on theAnophelesmosquitoes collected with the allelic and genotypic frequencies ofkdrgene determined. The multiple comparison Chi square test for proportions was performed with R version 3.3.3. Next, the observed heterozygosity, expected heterozygosity, and indices of fixation, and genetic differentiation were estimated. Finally, the Hardy–Weinberg equilibrium (EHW) was determined to assess whether panmixia exists in the different populations of mosquitoes of the agroecological zones under study.ResultsCarbamates, pyrethroids, organophosphorus and organochlorines use have been reported in all localities except Sô-Ava.Anopheles coluzziiwas strongly represented across all study localities. TheL1014Fallele was observed in the localities of Kétou, Cotonou and Zagnanado. Likewise, insecticide selection pressure of homozygous resistant individuals (L1014F/L1014F) was significantly higher in Kétou, Cotonou and Zagnanado (pvalue < 0.05). Surprisingly in Sô-Ava, a relatively high frequency of theL1014Fallele despite the reported absence of pesticide use was observed. All mosquito populations were found to be deficient in heterozygosity across the study sites (FIS< 0). No genetic differentiation (FST< 0) was observed in the localities of Zagnanado and Kétou.ConclusionThe survey on the use of insecticides showed that insecticide selection pressures differ across the investigated localities. It would be desirable to rotate or apply formulations of combined products with different modes of action. Doing so would enable a better management of resistant homozygous individuals, and mitigate the resistance effect of commonly used insecticides.
Combining dual-tree complex wavelets and multiresolution in iterative CT reconstruction with application to metal artifact reduction
Authors: Us Defne , Ruotsalainen Ulla , Pursiainen Sampsa 
Published: December 2019

Abstract
Background
This paper investigates the benefits of data filtering via complex dual wavelet transform for metal artifact reduction (MAR). The advantage of using complex dual wavelet basis for MAR was studied on simulated dental computed tomography (CT) data for its efficiency in terms of noise suppression and removal of secondary artifacts. Dual-tree complex wavelet transform (DT-CWT) was selected due to its enhanced directional analysis of image details compared to the ordinary wavelet transform. DT-CWT was used for multiresolution decomposition within a modified total variation (TV) regularized inversion algorithm.

Methods
In this study, we have tested the multiresolution TV (MRTV) approach with DT-CWT on a 2D polychromatic jaw phantom model with Gaussian and Poisson noise. High noise and sparse measurement settings were used to assess the performance of DT-CWT. The results were compared to the outcome of the single-resolution reconstruction and filtered back-projection (FBP) techniques as well as reconstructions with Haar wavelet basis.

Results
The results indicate that filtering of wavelet coefficients with DT-CWT effectively removes the noise without introducing new artifacts after inpainting. Furthermore, adoption of multiple resolution levels yield to a more robust algorithm compared to varying the regularization strength.

Conclusions
The multiresolution reconstruction with DT-CWT is also more robust when reconstructing the data with sparse projections compared to the single-resolution approach and Haar wavelets.
One opioid user saving another: the first study of an opioid overdose-reversal and naloxone distribution program addressing hard-to-reach drug scenes in Denmark
Authors: Thylstrup Birgitte , Hesse Morten , Jørgensen Marian , Thiesen Henrik 
Published: December 2019

Abstract
Background
Overdose education and naloxone distribution programs decrease opioid overdose deaths. However, no studies of such programs have been carried out in Denmark. The aim of this study was to evaluate the feasibility and the effect of a broader “training-the-trainers” model in low-threshold settings after participation in the “Danish Save Lives” [SL] program.

Methods
Between May 2013 and November 2015, 552 participants from four municipalities took part in the SL program. The program is built on the train-the-trainers model where a central trainer trains others (trainers), who in turn train others (helpers). Participants were 30 police officers (5%), 188 people who use opioids (34%), 23 significant others (4%), and 217 social workers (39%). Ninety-four participants could not be classified (17%). At follow-up, participants were interviewed to determine the number and outcomes of opioid overdoses. Logistic regression was used to assess predictors of treating an overdose.

Results
In all, 37 (7%) participants had intervened in 45 opioid overdose events (two trainers and 35 helpers). Detailed descriptions of the overdose event were available from 32 follow-up interviews (70%). In 16 cases, the person who intervened was already present at the site when the overdose occurred, and in 17 cases, the overdose victim recovered without complications. All overdose victims survived except one. People who used opioids were more likely to have treated an overdose than other participants (adjusted odds ratio [AOR] = 8.50, p = 0.001), and the likelihood of treating and overdose declined over time AOR = 0.37 (0.13, 0.93), p = 0.034).

Conclusions
Prevention programs that target people who use opioids are more likely to be effective than programs that target professionals, especially in high-risk settings that can be hard for paramedics to reach. A future goal is to explore how prevention programs can be adapted to new user groups.

Trial registration
The Danish Data Protection Agency, 2015-57-0002, Aarhus University, 2016-051-000001, 184, retrospectively registered