bluuebunny/crossref_metadata_2025_split huggingface dataset:
Motivating assessment item writers in medical programs: A qualitative study
Authors: Karthikeyan Sowmiya , O'Connor Elizabeth , Hu Wendy 
Published: September 2019

Abstract
Background

The challenge of generating sufficient quality items for medical student examinations is a common experience for medical program coordinators. Faculty development strategies are commonly used, but there is little research on the factors influencing medical educators to engage in item writing. To assist with designing evidence-based strategies to improve engagement, we conducted an interview study informed by self-determination theory (SDT) to understand educators’ motivations to write items.Methods

We conducted 11 semi-structured interviews with educators in an established medical program. Interviews were transcribed verbatim and underwent open coding and thematic analysis.Results

Major themes included; responsibility for item writing and item writer motivations, barriers and enablers; perceptions of the level of content expertise required to write items; and differences in the writing process between clinicians and non-clinicians.Conclusions

Our findings suggest that flexible item writing training, strengthening of peer review processes and institutional improvements such as improved communication of expectations, allocation of time for item writing and pairing new writers with experienced writers for mentorship could enhance writer engagement.
Clinical relevance of pulmonary non-tuberculous mycobacterial isolates in three reference centres in Belgium: a multicentre retrospective analysis.
Authors: Weygaerde Yannick Vande , Cardinaels Nina , Bomans Peter , Chin Taeyang , Boelens Jerina , André Emmanuel , Braeckel Eva Van , Lorent Natalie 
Published: September 2019

Abstract
Background/objectives: Assessing the clinical relevance of non-tuberculous mycobacteria (NTM) isolated from respiratory samples can be challenging. The epidemiology and pathogenicity of NTM species vary geographically. We aimed to outline the clinical relevance and associated radiological patterns of NTM species isolated in Belgium.
Methods: We performed a retrospective multicentre analysis of all patients identified from the laboratory database with > 1 respiratory sample growing NTM from January 2010 through December 2017. We collected clinical, radiological and microbiological data through medical record review and assessed clinical relevance according to ATS/IDSA criteria for NTM pulmonary disease (NTM-PD).
Results: Of the 384 unique patients, 60% were male, 56% had a smoking history and 61% had pre-existing lung disease. Mycobacterium avium complex (MAC), M. gordonae and M. xenopi were the most frequently isolated species: 53%, 15% and 8% respectively. 43% of patients met ATS/IDSA criteria, of whom 28% presented with fibrocavitary disease. Weight loss, night sweats, fatigue, cough and nodular bronchiectatic or fibrocavitary lesions on chest CT and positive acid-fast staining were more likely to be associated with NTM-PD. The species with the highest pathogenic potential were M. abscessus (11/12), M. malmoense (6/7) and M. intracellulare (41/64).
Conclusion: In our study, MAC was the most commonly isolated NTM species, but M. abscessus and M. malmoense showed the highest probability of being clinically relevant. Clinical relevance varied not only by species but also by the radiological findings on presentation. Clinicians should consider these elements in their treatment decision making. Prospective data including clinical outcome are needed to provide more robust evidence.
The phylodynamic of H1a genotype measles virus in Jiangsu province, China, 2005-2017
Authors: Lu Peishan , Hu Ying , Deng Xiuying , Sun Xiang , Guo Hongxiong 
Published: September 2019

Abstract
Background:
The change on the pressures during viruses evolving will cause changes in phylodynamic. To know phylodynamic characteristic of measles virus in high vaccination coverage era, the phylodynamic characteristic was analyzed using nucleoprotein gene sequences of measles viruses isolated from Jiangsu province of China from 2005 to 2017.
Methods:
Nucleoprotein gene sequences of measles viruses were used to analyze gene distance and construct phylogenetic tree with Markov chain Monte Carlo algorithm. The mean gene distance within each group was computed with MEGA7.0 software. The phylodynamic of measles virus circulating in Jiangsu province was constructed using Bayesian skyline plot analyses.
Results:
Our results showed that the decline trend is observed in the gene distance of nucleoprotein gene and effective population size of measles virus with time. Two clusters of H1a genotype shows multiple origins and the extinction of variants with time.
Conclusion:
These findings highlight that phylodynamic of measles viruses is a helpful tool to assess the effectiveness of epidemic control.
A community-based randomized trial for prevention and control of brucellosis among rural population: application of the PRECEDE planning model
Authors: Jahangiry Leila , Khazaee-Pool Maryam , Babazadeh Towhid , Sarbakhsh Parvin 
Published: September 2019

Abstract
Background: Brucellosis is one of the most frequently-occurring zoonotic diseases of veterinary and public health in developing countries. It affects human and animal health and has measurable effects on productive and reproductive performance of livestock. Thus the main purpose of this study is to develop a community-based intervention program for prevention and control of brucellosis. The two-arm parallel cluster randomized controlled trial investigated the effectiveness of an integrated prevention program over six months on brucellosis in a rural population in Ahar, East Azerbaijan, Iran. Health houses were selected of villages and randomly allocated into the intervention and the control groups (16 Health Houses in all, eight per arm). Participants were recruited via household health records in the health houses presented in the villages. The PRECEDE-PROCEED model was used to design, implement and evaluate of brucellosis prevention and control program. The appropriate strategy and intervention were matched with the project priority changes according to policies, resources, and organizational situations. Social support, knowledge, attitudes, self-efficacy, behavioral and environmental factors were measured at the baseline and 6-months follow-up. Generalized mixed effects-model was used to analyze data.
Results: A total of 400 individuals from the study answered the questions in the present study.
The mean age (SD) of the respondents in the intervention and control groups were 35.9 (11.87) and 37.28 (11.04) years, respectively. There were significant differences between intervention and control group for Precede model-base variables after six month of intervention program adjusted for adjusted for education, history of brucellosis and family history of brucellosis.
Conclusion: there is a need to consolidate collaborative efforts from the health and veterinary sectors, as well as to strengthen regular vaccination and financial resources to support farmers willing to compensate or offering slaughter facilities. This diagnostic study of educational and ecological factors influencing behaviors and environments related to brucellosis will identify where and how interventions can be most effective.
Prediction of the clinicopathological subtypes of breast cancers using Fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI
Authors: Ni Ming , Zhou Xiaoming , Liu Jingwei , Yu Haiyang , Gao Yuanxiang , Zhang Xuexi , Li Zhiming 
Published: September 2019

Abstract
Background

To investigate the feasibility of using Fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI for predicting clinicopathological subtypes of breast cancers.Methods

Patients who underwent breast magnetic resonance imaging were confirmed by retrieving our institutional picture archiving and communication system (PACS) between March 2013 and September 2017. Five clinicopathological subtypes were determined based on the status of ER, PR, HER2 and Ki-67 from the immunohistochemical test. Radiomic features of diffusion-weighted imaging were derived from the volume of interest (VOI) of each tumor. The Fisher discriminant analysis was performed for clinicopathological subtyping by using a backward selection method. To evaluate the diagnostic performance of radiomic features, ROC analyses were performed in differentiating between immunohistochemical biomarkers positive and negative group.Results

A total of 84 radiomic features of four statistics methods were involved after the preprocessing. An overall accuracy for predicting the clinicopathological subtypes was 96.4% by Fisher discriminant analysis. For predicting diverse clinicopathological subtypes, the prediction accuracies ranged from 92% to 100%. According to the cross-validation, the overall accuracy of the model was 82.1%, and accuracies of the model for predicting luminal A, luminal B Her2- , luminal B Her2+ , Her2 positive and triple negative were 79%, 77%, 88%, 92% and 73%, respectively. Based on ROC analysis, there were excellent diagnostic performances of radiomic features in differentiating between different status of ER, PR, HER2 and Ki-67.Conclusion

The Fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI is a reliable method for prediction of clinicopathological breast cancer subtypes.
DNMT1 inhibits hepatocellular carcinoma cells by altering the epigenetic modification of Marveld1 gene
Authors: Zhang Song Yan , Luo Qian , Wang Peng , Zhao Hao Ran , Xu Hai Tao , Zhao Liang , Qu Zhao Wei , Sun Jian Min , Zhang Yu Bao , Zheng Biao 
Published: September 2019

Abstract
Objective To study the effect of DNA methyltransferase (DNMT1) on Marveld1 in hepatocellular Carcinoma (HCC), and explore its role in the molecular mechanism of HCC occurrence and development.Methods The expression level of Dnmt1 and Marveld1 genes was detected by RT-PCR in the intraoperative pathological specimens. The human hepatoma Bel7402 and SMMC7721 cell lines down-regulated by DNMT1 gene expression were constructed by SiRNA transfection. The methylation level of Marveld1 promoter region was detected after RT-PCR and West-blot verification. The expression of Marveld1 gene, cell proliferation, invasion and change of cell cycle were detected by RT-PCR and West-blot. The expressions of P53, CyclinD1, P21 and P16 protein were detected by West-blot method.Results The expression of DNMT1 gene in human hepatocarcinoma tissues was higher than that in adjacent tissues. The methylation level of the Marveld1 gene promoter region in human hepatoma cell line down-regulated by DNMT1 gene expression was decreased, the expression level of Marveld1 gene was increased, and the proliferation and invasion ability of cells were weakened. The cell cycle was showed as G1-S phase arrest; P53 and P16 protein expressions were up-regulated, and CyclinD1 and P21 protein expressions were down-regulated.Conclusions Dnmt1 gene is highly expressed in human hepatocarcinoma tissues. Down-regulation of DNMT1 gene expression can decrease the methylation level of Marveld1 promoter region, up-regulate Marveld1 gene and human P53 and P16 proteins expressions, and down-regulate CyclinD1 and P21 proteins expressions, inhibit the proliferation and invasion of human hepatoma cells and can cause cell cycle G1-S arrest.
Enhancing Grain Yield and Operational Feasibility by Transplanting Young Hydroponically Grown Long‐Mat Rice Seedlings
Authors: Li Yuxiang , Luo Honghai , Yin Yongan , Wang Shaohua , Liu Zhenghui , Tang She , Chen Lin , Ding Chengqiang , Ding Yanfeng , Li Ganghua 
Published: September 2019

Seedling transplanting is one of the predominant rice production systems in China. The production of hydroponically grown long‐mat rice seedlings (HLMS) is a novel seedling cultivation method that reduces labor costs and improves efficiency. There is an urgent need to explore the optimum seedling age that maximizes grain yield from HLMS. Experiments were conducted to investigate the effects of seedling age on the seedling quality, field growth characteristics and grain yield of rice grown from HLMS. The grain yield was higher for young seedlings (13 d) than for older seedlings (27 d) as a result of robust seedling quality, increased mechanical transplanting quality, slight transplanting shock, sufficient tillers and increased panicle numbers in both cultivars when grown from HLMS under normal seeding density, and there was no significant difference in grain yield between transplanted 13‐ and 20‐d‐old seedlings. Moreover, the decreased yield in Wuyunjing24 might due to the reduced number of spikelets per panicle in old seedlings. In addition, the force of root entwining was significantly enhanced with increasing seedling age for both seedling cultivation methods and cultivars, and it was significantly higher for HLMS than for conventional mat seedlings raised in soil (CMSS). In general, transplanting young seedlings (13–20 d) by the HLMS method under normal seeding density brings better plant performance and higher yield than does transplanting older seedlings; relative to CMSS, HLMS increased the flexibility of seedling age (>7 d) and operational feasibility, which can be mainly ascribed to the enhanced force of root entwining.Core Ideas

Hydroponically grown long‐mat seedlings significantly enhanced the force of root entwining (>8 kilograms per block), enabling rice seedlings of different ages to withstand farming operations.
Relative to conventional mat seedlings raised in soil, hydroponically grown long‐mat seedlings increased the flexibility of seedling age at transplant (>7 d).
Transplanting young seedlings (13–20 d) by the hydroponically grown long‐mat seedlings method achieved higher grain yield than did transplating older seedlings (27 d) under normal seeding density.
Predicting Nitrogen Losses in Potato Crop with Soil Nitrogen and Plant Tests
Authors: Giletto Claudia Marcela , Calvo Nahuel Reussi , Echeverría Hernán 
Published: September 2019

There is a lack of information on how to determine N‐use efficiency and monitoring and diagnosing N losses in irrigated potato (Solanum tuberosumL.) production. This study was conducted to determine and validate a simple model to estimate inorganic N leaching losses (Nlosses) from gravitational water and to determine Nlossesthresholds using the soil N and canopy sensor tests. We conducted field experiments (n= 6) from 2008 to 2012 to evaluate the effects of N rates and/or managements and gravitational water on tuber yield, crop N uptake (Nuptake) and Nlosseson the cultivar Innovator in the Argentinean Pampas. The N nutrition index (NNI), normalized chlorophyll meter reading (NNI‐CM), relative chlorophyll meter reading (CMr), and relative normalized difference vegetative index (NDVIr) were determined 70 d after planting. Tuber yield, residual N, and Nlossesvaried from 40.8 to 70.3 t ha−1, 23.2 to 78.7 kg N ha−1and 6.4 to 219.4 kg N ha−1, respectively. The Nlosseswere directly associated with the amount of gravitational water in the soil profile (r2= 0.79). Threshold values of 255 kg N ha−1for N available, 1.0 for NNI, 1.03 for NNI‐CM, 0.94 for CMr and 0.98 for NDVIr were defined. We determined linear increases in Nlossesabove these thresholds (r2= 0.75, 0.35, 0.53, 0.40, and 0.46, respectively). High N rates and gravitational water increased the N losses in potato crops under irrigation. This information could be useful to adjust N fertilizer recommendation and monitoring the Nlossesin potato crops under irrigation.Core IdeasInformation on how to monitor and diagnose N losses in irrigated potato production is lacking.This study estimates N losses from gravitational water, soil N, and canopy sensor tests.The aim is to predict N‐loss thresholds using soil N and canopy sensor tests.N losses were directly associated with the amount of gravitational water in the soil profile.
Gross Primary Production Estimation in Crops Using Solely Remotely Sensed Data
Authors: Peng Yi , Kira Oz , Nguy‐Robertson Anthony , Suyker Andrew , Arkebauer Timothy , Sun Ying , Gitelson Anatoly A. 
Published: September 2019

Gross primary production (GPP) is a measure for crop productivity, indicating yield and expressing C exchange of agro‐ecosystems. A multitude of satellite sensors at varying spatial and spectral resolution brings a possibility to use remotely sensed data for regional and global GPP estimation. More work is still needed to develop algorithms for GPP estimation applicable to multiple, if not all, vegetation types, phenological phases, and environmental conditions. This study employed neural networks (NN), multiple linear regressions (MLR), and vegetation indices (VI) to develop algorithms for GPP estimation based solely on remotely sensed data in two crops, maize (Zea mays L.) and soybean [Glycine max (L.) Merr.], with contrasting canopy architectures, leaf structures, and photosynthetic pathways. The focus of the study was to devise algorithms not requiring re‐parameterization for different crop species. Data used in the models included in situ hyperspectral reflectance and satellite surface reflectance products. For the tested NN, MLR, and VI algorithms, the bands selected to obtain minimal errors in maize and soybean combined were mainly located in red edge and near infrared (NIR) spectral regions. For both in situ reflectance and satellite surface reflectance, a NN estimated GPP with normalized root mean square errors (NRMSE) below 14 and 18.7%, respectively, and VI using bands in red edge and NIR with NRMSE 15.6 and 20.4%, respectively. The results showed that the models based on the red edge and NIR bands may facilitate accurate assessments of crop GPP at multiple scales, from close range to satellite platforms.Core Ideas

The models using remotely sensed data allow accurate estimation of gross primary production in two crops.
The optimal bands for gross primary production estimation in two crops were in near infrared and red edge regions.
Vegetation indices with red edge and near infrared reflectance were generic for maize and soybean.
Straw Mulching under a Drip Irrigation System Improves Maize Grain Yield and Water Use Efficiency
Authors: Zhou Baoyuan , Ma Di , Sun Xuefang , Ding Zaisong , Li Congfeng , Ma Wei , Zhao Ming 
Published: September 2019

ABSTRACTReasonable use of water is required for the sustainable development of maize production in the North China Plain (NCP). In this study, straw mulching (SM) was evaluated in a 2‐yr field experiment to determine whether its effect on maize (Zea maysL.) yield and water use efficiency (WUE) differed under different irrigation systems. Compared with no mulching (NM) treatment, SM increased maize yield by 10.6 and 12.5% under a drip irrigation system in 2016 and 2017, respectively, which was mainly attributed to an 11.7 and 13.5% increase in total dry matter (DM). The increased soil water content in the 0‐ to 40‐cm layer at the six‐leaf (V6), silking (R1), and maturity (R6) stages for SM improved the soil mineral N content (Nmin) in that layer and then increased the N accumulation from V6 to R1 and post‐silking by 7.6 and 21.1% averaged over 2 yr compared with NM, respectively. The enhanced N accumulation for SM increased the leaf area index and DM accumulation rate, which increased the DM accumulation from V12 to R1 and post‐silking by 16.2 and 16.4% averaged over 2 yr compared with NM, respectively, and then the grain number and grain weight. Straw mulching also improved the WUE under the drip irrigation system due to the greater grain yield and 6.1% lower water consumption. This demonstrated that SM combined with the drip irrigation system effectively improved the yield and WUE of maize due to improved DM and N accumulation promoted by the increased water content and Nminin the upper soil layers.
Impacts of Intensified Cropping Systems on Soil Water Use by Spring Wheat
Authors: Halvorson Jonathan J. , Archer David W. , Liebig Mark A. , Yeater Kathleen M. , Tanaka Donald L. 
Published: September 2019

In semiarid dryland farming regions, No‐till and intensified crop rotations may improve water use. Our objective was to determine water use efficiency (WUE) and precipitation use efficiency (PUE) for spring wheat (Triticum aestivum L.; SW) grown in crop sequences representing different levels of intensification, under minimum (Min‐till) or No‐till. Root zone (0–122 cm) water at planting (SWP) was 2.76 cm higher for two‐ and three‐phase sequences under Min‐till than continuous spring wheat (CSW), and sequences with fallow averaged 2.65 cm higher than those without. Conversely, SWP was unaffected by sequence under No‐till, with less effect of fallow. Root zone water at harvest was unaffected by the number of crop phases or fallow under Min‐till. However, values for CSW exceeded the two‐ or three‐phase sequences by 1.57 and 2.53 cm under No‐till, and sequences without fallow averaged 1.52 cm more than those with fallow. The highest WUE (8.4 kg grain ha−1 mm−1 water) was observed when SW was grown in three‐phase sequences compared with 7.7 kg grain ha−1 mm−1 water, for CSW and SW‐fallow. Spring wheat under Min‐till had higher WUE in sequences with fallow, but no effects of fallow occurred with No‐till. The lowest PUE (near 3 kg grain ha−1 mm−1 precipitation) and no effects of tillage were found in sequences with fallow. However, SW in continuously cropped sequences had PUE between 5.5 and 6.4 kg grain ha−1 mm−1 precipitation and was higher under No‐till. Both WUE and PUE are affected by intensification but may also be influenced by patterns of weather.Core Ideas
Profile water varied as an interaction between crop sequence and tillage.
With fallow, soil water changed little the winter prior to planting.
Crop water use and yields were lower under continuous cropping than with fallow.
Water use efficiency was highest for three‐phase sequences but varied with yield.
Continuous cropping resulted in more efficient use of precipitation over the study.
Recalibration of Sensors in One of The World's Longest Running Automated Soil Moisture Monitoring Networks
Authors: Zhang Yongyong , Ochsner Tyson E. , Fiebrich Christopher A. , Illston Bradley G. 
Published: September 2019

Obtaining accurate soil moisture data from sensors in automated monitoring networks is critical as these data are increasingly used for research in soil hydrology, ecohydrology, and related disciplines. One of the earliest such networks is the Oklahoma Mesonet, which monitors soil matric potential using heat dissipation sensors. Various calibration equations have been proposed for those sensors, and there is a need to compare and validate the performance of those equations, especially for matric potentials < –150 kPa. A laboratory experiment was conducted in silt loam soil using a sand‐kaolin box and a pressure plate apparatus with matric potentials ranging from 0 to –1500 kPa. The calibration equations included Starks’ equation, Flint et al.'s equation, Schneider et al.'s equation, and a new logistic equation. The upper limit of the sensors was ‐9 kPa, and the sensors remained responsive at ‐1500 kPa matric potential. The logistic equation produced the lowest root mean squared error (34 kPa), followed by Flint et al.'s equation (192 kPa), Starks’ equation (295 kPa), and Schneider et al.'s equation (463 kPa). After recalibration of the coefficients in the three preexisting equations, their performances improved, with all RMSE values ≤ 251 kPa; however, the logistic equation still provided superior accuracy. The logistic equation effectively removed an ∼ 0.02 cm3 cm−3 positive bias in soil water content that resulted from use of the original parameterization of Schneider et al.'s equation. This logistic equation is recommended for use with past and future data from the Oklahoma Mesonet's heat dissipation sensors.Core Ideas
Soil matric potential data from the Oklahoma Mesonet are widely used.
Those data are estimated using a calibration equation shown here to be inaccurate.
The logistic equation developed here produces more accurate matric potential estimates.