bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptive-size dictionary learning using information theoretic criteria for image reconstruction from undersampled k-space data in low field magnetic resonance imaging
Authors: Ahishakiye Emmanuel , Van Gijzen Martin Bastiaan , Tumwiine Julius , Obungoloch Johnes 
Published: June 2020

Abstract
Background
Magnetic resonance imaging (MRI) is a safe non-invasive and nonionizing medical imaging modality that is used to visualize the structure of human anatomy. Conventional (high-field) MRI scanners are very expensive to purchase, operate and maintain, which limit their use in many developing countries. This study is part of a project that aims at addressing these challenges and is carried out by teams from Mbarara University of Science and Technology (MUST) in Uganda, Leiden University Medical Center (LUMC) in the Netherlands, Delft University of Technology (TU Delft) in the Netherlands and Pennsylvania State University (PSU) in the USA. These are working on developing affordable, portable and low-field MRI scanners to diagnose children in developing countries with hydrocephalus. The challenges faced by the teams are that the low-field MRI scanners currently under development are characterized by low Signal-to-Noise Ratio (SNR), and long scan times.

Methods
We propose an algorithm called adaptive-size dictionary learning algorithm (AS-DLMRI) that integrates information-theoretic criteria (ITC) and Dictionary learning approaches. The result of the integration is an adaptive-size dictionary that is optimal for any input signal. AS-DLMRI may help to reduce the scan time and improve the SNR of the generated images, thereby improving the image quality.

Results
We compared our proposed algorithm AS-DLMRI with adaptive patch-based algorithm known as DLMRI and non-adaptive CSMRI technique known as LDP. DLMRI and LDP have been used as the baseline algorithms in other related studies. The results of AS-DLMRI are consistently slightly better in terms of PSNR, SNR and HFEN than for DLMRI, and are significantly better than for LDP. Moreover, AS-DLMRI is faster than DLMRI.

Conclusion
Using a dictionary size that is appropriate to the input data could reduce the computational complexity, and also the construction quality since only dictionary atoms that are relevant to the task are included in the dictionary and are used during the reconstruction. However, AS-DLMRI did not completely remove noise during the experiments with the noisy phantom. Our next step in our research is to integrate our proposed algorithm with an image denoising function.
Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol
Authors: Gooding Kim M. , Lienczewski Chrysta , Papale Massimo , Koivuviita Niina , Maziarz Marlena , Dutius Andersson Anna-Maria , Sharma Kanishka , Pontrelli Paola , Garcia Hernandez Alberto , Bailey Julie , Tobin Kay , Saunavaara Virva , Zetterqvist Anna , Shelley David , Teh Irvin , Ball Claire , Puppala Sapna , Ibberson Mark , Karihaloo Anil , Metsärinne Kaj , Banks Rosamonde E. , Gilmour Peter S. , Mansfield Michael , Gilchrist Mark , de Zeeuw Dick , Heerspink Hiddo J. L. , Nuutila Pirjo , Kretzler Matthias , Welberry Smith Matthew , Gesualdo Loreto , Andress Dennis , Grenier Nicolas , Shore Angela C. , Gomez Maria F. , Sourbron Steven ,   for the BEAt-DKD consortium
Published: June 2020

AbstractBackgroundDiabetic kidney disease (DKD) remains one of the leading causes of premature death in diabetes. DKD is classified on albuminuria and reduced kidney function (estimated glomerular filtration rate (eGFR)) but these have modest value for predicting future renal status. There is an unmet need for biomarkers that can be used in clinical settings which also improve prediction of renal decline on top of routinely available data, particularly in the early stages. The iBEAt study of the BEAt-DKD project aims to determine whether renal imaging biomarkers (magnetic resonance imaging (MRI) and ultrasound (US)) provide insight into the pathogenesis and heterogeneity of DKD (primary aim) and whether they have potential as prognostic biomarkers in DKD (secondary aim).MethodsiBEAt is a prospective multi-centre observational cohort study recruiting 500 patients with type 2 diabetes (T2D) and eGFR ≥30 ml/min/1.73m2. At baseline, blood and urine will be collected, clinical examinations will be performed, and medical history will be obtained. These assessments will be repeated annually for 3 years. At baseline each participant will also undergo quantitative renal MRI and US with central processing of MRI images. Biological samples will be stored in a central laboratory for biomarker and validation studies, and data in a central data depository. Data analysis will explore the potential associations between imaging biomarkers and renal function, and whether the imaging biomarkers improve the prediction of DKD progression. Ancillary substudies will: (1) validate imaging biomarkers against renal histopathology; (2) validate MRI based renal blood flow measurements against H2O15positron-emission tomography (PET); (3) validate methods for (semi-)automated processing of renal MRI; (4) examine longitudinal changes in imaging biomarkers; (5) examine whether glycocalyx and microvascular measures are associated with imaging biomarkers and eGFR decline; (6) explore whether the findings in T2D can be extrapolated to type 1 diabetes.DiscussioniBEAt is the largest DKD imaging study to date and will provide valuable insights into the progression and heterogeneity of DKD. The results may contribute to a more personalised approach to DKD management in patients with T2D.Trial registrationClinicaltrials.gov(NCT03716401).
Potential value of three-dimensional ultrasonography in diagnosis of diabetic nephropathy in Chinese diabetic population with kidney injury
Authors: Li Nan , Wang Yi-ru , Tian Xiao-qi , Lin Lin , Liang Shu-yuan , Li Qiu-yang , Fei Xiang , Tang Jie , Luo Yu-kun 
Published: June 2020

Abstract
Background
To explore the potential value of three-dimensional ultrasonography (3DUS) and contrast-enhanced ultrasound (CEUS) in the diagnosis of diabetic nephropathy (DN) in Chinese diabetic patients with kidney injury.

Methods
Patients with type 2 diabetes mellitus and kidney injury in our hospital were enrolled, and the clinical characteristics as well as the laboratory data of patients were collected; 3DUS and CEUS were used to evaluate the morphological structure and blood perfusion of kidneys. Eligible patients were categorized into two groups based on renal biopsy results: DN group and non-diabetic renal diseases (NDRD) group. Correlation analysis and logistic regression analysis were applied to identify the risk factors of DN development.

Results
A total of 115 patients aged from 24 to 78 years old were recruited in the experiment, of which 64 patients (55.65%) and 51 patients (44.35%) were in the DN group and NDRD group, respectively. After correction to CKD stage, BMI and right kidney volume index were retained to identify patients with DN. The ROC of the logistic regression model had an AUC of 0.703 (95% CI: 0.591–0.815) and it was higher than both indicators.

Conclusion
3DUS has potential value in the diagnosis of diabetic nephropathy in Chinese diabetic population with kidney injury and may act as an auxiliary diagnosis for DN. More prospective and well-designed studies with larger samples are needed to verify the result.
Integration of genomics, metagenomics, and metabolomics to identify interplay between susceptibility alleles and microbiota in adenoma initiation
Authors: Moskowitz Jacob E. , Doran Anthony G. , Lei Zhentian , Busi Susheel B. , Hart Marcia L. , Franklin Craig L. , Sumner Lloyd W. , Keane Thomas M. , Amos-Landgraf James M. 
Published: June 2020

Abstract
Background
Colorectal cancer (CRC) is a multifactorial disease resulting from both genetic predisposition and environmental factors including the gut microbiota (GM), but deciphering the influence of genetic variants, environmental variables, and interactions with the GM is exceedingly difficult. We previously observed significant differences in intestinal adenoma multiplicity between C57BL/6 J-ApcMin (B6-Min/J) from The Jackson Laboratory (JAX), and original founder strain C57BL/6JD-ApcMin (B6-Min/D) from the University of Wisconsin.

Methods
To resolve genetic and environmental interactions and determine their contributions we utilized two genetically inbred, independently isolated ApcMin mouse colonies that have been separated for over 20 generations. Whole genome sequencing was used to identify genetic variants unique to the two substrains. To determine the influence of genetic variants and the impact of differences in the GM on phenotypic variability, we used complex microbiota targeted rederivation to generate two Apc mutant mouse colonies harboring complex GMs from two different sources (GMJAX originally from JAX or GMHSD originally from Envigo), creating four ApcMin groups. Untargeted metabolomics were used to characterize shifts in the fecal metabolite profile based on genetic variation and differences in the GM.

Results
WGS revealed several thousand high quality variants unique to the two substrains. No homozygous variants were present in coding regions, with the vast majority of variants residing in noncoding regions. Host genetic divergence between Min/J and Min/D and the complex GM additively determined differential adenoma susceptibility. Untargeted metabolomics revealed that both genetic lineage and the GM collectively determined the fecal metabolite profile, and that each differentially regulates bile acid (BA) metabolism. Metabolomics pathway analysis facilitated identification of a functionally relevant private noncoding variant associated with the bile acid transporter Fatty acid binding protein 6 (Fabp6). Expression studies demonstrated differential expression of Fabp6 between Min/J and Min/D, and the variant correlates with adenoma multiplicity in backcrossed mice.

Conclusions
We found that both genetic variation and differences in microbiota influences the quantitiative adenoma phenotype in ApcMin mice. These findings demonstrate how the use of metabolomics datasets can aid as a functional genomic tool, and furthermore illustrate the power of a multi-omics approach to dissect complex disease susceptibility of noncoding variants.
Model of genetic and environmental factors associated with type 2 diabetes mellitus in a Chinese Han population
Authors: Li Zheng , Ye Cheng-yin , Zhao Tian-Yu , Yang Lei 
Published: June 2020

Abstract
Background
Type 2 diabetes mellitus (T2DM) is a metabolic disorder which accounts for high morbidity and mortality due to complications like renal failure, amputations, cardiovascular disease, and cerebrovascular events.

Methods
We collected medical reports, lifestyle details, and blood samples of individuals and used the polymerase chain reaction-ligase detection reaction method to genotype the SNPs, and a visit was conducted in August 2016 to obtain the incidence of Type 2 diabetes in the 2113 eligible people. To explore which genes and environmental factors are associated with type 2 diabetes mellitus in a Chinese Han population, we used elastic net to build a model, which is to explain which variables are strongly associated with T2DM, rather than predict the occurrence of T2DM.

Result
The genotype of the additive of rs964184, together with the history of hypertension, regular intake of meat and waist circumference, increased the risk of T2DM (adjusted OR = 2.38, p = 0.042; adjusted OR = 3.31, p < 0.001; adjusted OR = 1.05, p < 0.001). The TT genotype of the additive and recessive models of rs12654264, the CC genotype of the additive and dominant models of rs2065412, the TT genotype of the additive and dominant models of rs4149336, together with the degree of education, regular exercise, reduced the risk of T2DM (adjusted OR = 0.46, p = 0.017; adjusted OR = 0.53, p = 0.021; adjusted OR = 0.59, p = 0.021; adjusted OR = 0.57, p = 0.01; adjusted OR = 0.59, p = 0.021; adjusted OR = 0.57, p = 0.01; adjusted OR = 0.50, p = 0.007; adjusted OR = 0.80, p = 0.032) .

Conclusion
Eventually we identified a set of SNPs and environmental factors: rs5805 in the SLC12A3, rs12654264 in the HMGCR, rs2065412 and rs414936 in the ABCA1, rs96418 in the ZPR1 gene, waistline, degree of education, exercise frequency, hypertension, and the intake of meat. Although there was no interaction between these variables, people with two risk factors had a higher risk of T2DM than those only having one factor. These results provide the theoretical basis for gene and other risk factors screening to prevent T2DM.
Socioeconomic inequality in tobacco expenditure in Iran: a cross-sectional analysis at national and subnational levels
Authors: Rezaei Satar , Pulok Mohammad Habibullah , Ebrahimi Mohammad 
Published: June 2020

Abstract
Background
Tobacco expenditure has adverse impacts on expenditure on basic needs and resource allocation of the households. Using data from a nationally representative survey, we measured socioeconomic inequality in tobacco expenditure as the share of household budget (TEHB) and explained its main determinants among Iranian households at the national and sub-national levels.

Methods
This cross-sectional study used data from the Iranian Household Income and Expenditure Survey (IHIES), 2018. We included a total of 7649 households with tobacco expenditure more than zero in the analysis. Province-level data on the Human Development Index (HDI) was obtained from the Institute for Management Research at Radbound University. The concentration curve (CC) and the concentration index (C) were used to measure socioeconomic inequality in TEHB at national and sub-national levels. The C was decomposed to identify the factors explaining the observed socioeconomic inequality in TEHB.

Results
At the national level, households with at least one smoker spent more than 5% of their budget for tobacco consumption in the last month. Households from the urban areas allocated less of their budgets on tobacco products compared to rural households (4.6% vs. 5.8%). Overall, TEHB was more concentrated among the poorer households (C = 0.1423, 95% CI: − 0.1552 to − 0.1301). In other words, the distribution of TEHB was pro-poor in Iran. Pro-poor inequality in TEHB was also found in urban (C = − 0.1707, 95% CI: − 0.1998 to − 0.1516) and rural (C = − 0.1314, 95% CI: − 0.1474 to − 0.1152) areas. We also found that pro-poor inequalities were higher in Iranian provinces with low HDI. The decomposition results indicate that wealth and education were the main factors contributing to the concentration of TEHB among the poorer households.

Conclusion
This study found that TEHB was disproportionality concentrated among poorer households in Iran. The extent of inequality in TEHB was higher in urban areas and less developed provinces. Designing and implementing tobacco control interventions to decrease the smoking prevalence and increase smoking cessation could protect worse-off households against the financial burden of tobacco spending.
Establishing seasonal and alert influenza thresholds in Morocco
Authors: Rguig Ahmed , Cherkaoui Imad , McCarron Margaret , Oumzil Hicham , Triki Soumia , Elmbarki Houria , Bimouhen Abderrahman , El Falaki Fatima , Regragui Zakia , Ihazmad Hassan , Nejjari Chakib , Youbi Mohammed 
Published: June 2020

Abstract
Background
Several statistical methods of variable complexity have been developed to establish thresholds for influenza activity that may be used to inform public health guidance. We compared the results of two methods and explored how they worked to characterize the 2018 influenza season performance–2018 season.

Methods
Historical data from the 2005/2006 to 2016/2018 influenza season performance seasons were provided by a network of 412 primary health centers in charge of influenza like illness (ILI) sentinel surveillance. We used the WHO averages and the moving epidemic method (MEM) to evaluate the proportion of ILI visits among all outpatient consultations (ILI%) as a proxy for influenza activity. We also used the MEM method to evaluate three seasons of composite data (ILI% multiplied by percent of ILI with laboratory-confirmed influenza) as recommended by WHO.

Results
The WHO method estimated the seasonal ILI% threshold at 0.9%. The annual epidemic period began on average at week 46 and lasted an average of 18 weeks. The MEM model estimated the epidemic threshold (corresponding to the WHO seasonal threshold) at 1.5% of ILI visits among all outpatient consultations. The annual epidemic period began on week 49 and lasted on average 14 weeks. Intensity thresholds were similar using both methods. When using the composite measure, the MEM method showed a clearer estimate of the beginning of the influenza epidemic, which was coincident with a sharp increase in confirmed ILI cases.

Conclusions
We found that the threshold methodology presented in the WHO manual is simple to implement and easy to adopt for use by the Moroccan influenza surveillance system. The MEM method is more statistically sophisticated and may allow a better detection of the start of seasonal epidemics. Incorporation of virologic data into the composite parameter as recommended by WHO has the potential to increase the accuracy of seasonal threshold estimation.
Estimates of female genital mutilation/cutting in the Netherlands: a comparison between a nationwide survey in midwifery practices and extrapolation-model
Authors: Kawous Ramin , van den Muijsenbergh Maria E. T. C. , Geraci Diana , Hendriks Kyra R. M. , Ortensi Livia E. , Hilverda Femke , Burdorf Alex 
Published: June 2020

Abstract
Background
Owing to migration, female genital mutilation or cutting (FGM/C) has become a growing concern in host countries in which FGM/C is not familiar. There is a need for reliable estimates of FGM/C prevalence to inform medical and public health policy. We aimed to advance methodology for estimating the prevalence of FGM/C in diaspora by determining the prevalence of FGM/C among women giving birth in the Netherlands.

Methods
Two methods were applied to estimate the prevalence of FGM/C in women giving birth: (I) direct estimation of FGM/C was performed through a nationwide survey of all midwifery practices in the Netherlands and (II) the extrapolation model was adopted for indirect estimation of FGM/C, by applying population-based-survey data on FGM/C in country of origin to migrant women who gave birth in 2018 in the Netherlands.

Results
A nationwide survey among primary care midwifery practices that provided care for 57.5% of all deliveries in 2018 in the Netherlands, reported 523 cases of FGM/C, constituting FGM/C prevalence of 0.54%. The indirect estimation of FGM/C in an extrapolation-model resulted in an estimated prevalence of 1.55%. Possible reasons for the difference in FGM/C prevalence between direct- and indirect estimation include that the midwives were not being able to recognize, record or classify FGM/C, referral to an obstetrician before assessing FGM/C status of women and selective responding to the survey. Also, migrants might differ from people in their country of origin in terms of acculturation toward discontinuation of the practice. This may have contributed to the higher indirect-estimation of FGM/C compared to direct estimation of FGM/C.

Conclusions
The current study has provided insight into direct estimation of FGM/C through a survey of midwifery practices in the Netherlands. Evidence based on midwifery practices data can be regarded as a minimum benchmark for actual prevalence among the subpopulation of women who gave birth in a given year.
Arthroscopic tri-pulley Technology reduction and internal fixation of pediatric Tibial Eminence fracture: a retrospective analysis
Authors: Zhang Liang , Zhang Li , Zheng Jiang , Ren Bo , Kang Xin , Zhang Xian , Dang Xiaoqian 
Published: June 2020

Abstract
Background
Fixing a tibial eminence fracture with a tri-pulley is a new technique. The purpose of this study was to present the early clinical outcome of arthroscopic tri-pulley suture fixation for tibial eminence fractures in children.

Methods
Twenty-one pediatric patients with type II or type III anterior tibial eminence fractures were included in this retrospective study. All Patients underwent surgical fixation by tri-pulley technology and were followed up for at least 24 months. They were evaluated preoperatively and postoperatively by physical, X-ray, and computed tomography (CT) examination and subjectively with the International Knee Documentation Committee (IKDC), and Lysholm questionnaires.

Results
The patients included 12 males and 9 females; mean age, 12.5 years (range, 8 ~ 16 years). They were followed-up for a median of 27 months (range, 24 ~ 39 months). We did not find post-operative instability in any of the patients by physical examination. The KT-2000 difference of both knees decreased from 9.3 ± 1.2 mm preoperatively to 2.6 ± 0.8 mm 24 months postoperatively (P < 0.001); the IKDC subjective knee evaluation score improved from 43.1 ± 13.2 preoperatively to 83.8 ± 6.3 postoperatively (P < 0.001); and Lysholm improved from 48.3 ± 6.21 to 87.1 ± 9.8 (P < 0.001). No unhealed fractures or epiphyseal damage were reported in the postoperative X-ray and CT.

Conclusions
Arthroscopic tri-pulley fixation technology may provide a suitable technique for repair of tibial eminence fractures in skeletally immature patients.

Level of evidence
Case series; Level of evidence IV.
The impact of the COVID-19 pandemic on final year medical students in the United Kingdom: a national survey
Authors: Choi Byung , Jegatheeswaran Lavandan , Minocha Amal , Alhilani Michel , Nakhoul Maria , Mutengesa Ernest 
Published: June 2020

Abstract
Background
The coronavirus disease (COVID-19) global pandemic has resulted in unprecedented public health measures. This has impacted the UK education sector with many universities halting campus-based teaching and examinations. The aim of this study is to identify the impact of COVID-19 on final year medical students’ examinations and placements in the United Kingdom (UK) and how it might impact their confidence and preparedness going into their first year of foundation training.

Methods
A 10-item online survey was distributed to final year medical students across 33 UK medical schools. The survey was designed by combining dichotomous, multiple choice and likert response scale questions. Participants were asked about the effect that the COVID-19 global pandemic had on final year medical written exams, electives, assistantships and objective structured clinical examinations (OSCEs). The survey also explored the student’s confidence and preparedness going into their first year of training under these new unprecedented circumstances.

Results
Four hundred forty students from 32 UK medical schools responded. 38.4% (n = 169) of respondents had their final OSCEs cancelled while 43.0% (n = 189) had already completed their final OSCEs before restrictions. 43.0% (n = 189) of assistantship placements were postponed while 77.3% (n = 340) had electives cancelled. The impact of COVID-19 on OSCEs, written examinations and student assistantships significantly affected students’ preparedness (respectively p = 0.025, 0.008, 0.0005). In contrast, when measuring confidence, only changes to student assistantships had a significant effect (p = 0.0005). The majority of students feel that measures taken during this pandemic to amend their curricula was necessary. Respondents also agree that assisting in hospitals during the outbreak would be a valuable learning opportunity.

Conclusions
The impact on medical student education has been significant, particularly affecting the transition from student to doctor. This study showed the disruptions to student assistantships had the biggest effect on students’ confidence and preparedness. For those willing to assist in hospitals to join the front-line workforce, it is crucial to maintain their wellbeing with safeguards such as proper inductions, support and supervision.