bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tumor Location and Type Affect Local Recurrence and Joint Damage in Tenosynovial Giant Cell Tumor: A Multi-center Study
Authors: Ota Takehiro , Nishida Yoshihiro , Ikuta Kunihiro , Tsukushi Satoshi , Yamada Kenji , Kozawa Eiji , Urakawa Hiroshi , Imagama Shiro 
Published: June 2021

Abstract
Purpose: Osteochondral destruction and high recurrence rate after surgery are major concerns during the treatment course of tenosynovial giant cell tumor. The aims of this study were to elucidate rates of local recurrence and osteochondral destruction, and demographic factors correlated with osteochondral destruction and recurrence rate after surgery. Methods: Eighty surgically treated patients (knee: 49, ankle and foot: 12, hip: 10, others: 9) were included in this study. Factors including age, disease type (diffuse/localized), location, existence of osteochondral destruction were analyzed to be correlated with local recurrence or development/progression of osteochondral destruction. Results: The 5-year local recurrence free survival rate was 71.4 %. Diffuse type (n=59, localized: n=21) (P=0.023) and knee location (P=0.002) were independent risk factors for local recurrence. Diffuse type (P=0. 009) was a significant risk factor, and knee location (P=0. 001) was a negative factor for osteochondral destruction at the initial examination. Progression of osteochondral destruction was observed more often in cases with local recurrence (P=0.040) and findings of osteochondral destruction at the initial examination (P=0.029).Conclusions: Diffuse type is a factor that should be noted for both local recurrence and osteochondral destruction, and local recurrence occurs but osteochondral destruction is less observed for knee location.
A High-continuity and Annotated Tomato Reference Genome
Authors: Su Xiao , Wang Baoan , Geng Xiaolin , Du Yuefan , Yang Qinqin , Liang Bin , Meng Ge , Gao Qiang , Yang Wencai , Zhu Yingfang , Lin Tao 
Published: June 2021

Abstract
Background: Genetic and functional genomics studies require a high-quality genome assembly. Tomato (Solanum lycopersicum), an important horticultural crop, is an ideal model species for the study of fruit development. Results: Here, we assembled an updated reference genome of S. lycopersicum cv. Heinz 1706 that was 799.09 Mb in length, containing 34,384 predicted protein-coding genes and 65.66% repetitive sequences. By comparing the genomes of S. lycopersicum and S. pimpinellifolium LA2093, we found a large number of genomic fragments probably associated with human selection, which may have had crucial roles in the domestication of tomato. We also used a recombinant inbred line (RIL) population to generate a high-density genetic map with high resolution and accuracy. Using these resources, we identified a number of candidate genes that were likely to be related to important agronomic traits in tomato. Conclusion:Our results offer opportunities for understanding the evolution of the tomato genome and will facilitate the study of genetic mechanisms in tomato biology.
The impact of “4+7” volume based drugs procurement on the volume, expenditures, and daily costs of antihypertensive drugs in Shenzhen, China: a interrupted time series analysis
Authors: Yang Ying , Tong Ruiwen , Yin Shicheng , Mao Lining , Xu Luxinyi , Hao Siyu , Mao Zongfu 
Published: June 2021

Abstract
Background: On January 2019, Chinese government implemented the first round of the National Centralized Drug Procurement (NCDP) pilot of 25 drugs in 4 municipalities and 7 sub-provincial cities in mainland China, referred to as “4+7” policy. In the “4+7” policy, 7 antihypertensive drugs were included. This study was conducted to evaluate the impact of “4+7” policy on the use of policy-related antihypertensive drugs. Method: This study applied single-group Interrupted Time Series (ITS) design. We used drug purchasing data from the Centralized Drug Procurement Survey in Shenzhen 2019, covering 24 months from January 2018 to December 2019. Antihypertensive drugs related to “4+7” policy were selected as study samples, including 7 antihypertensive drugs in the “4+7” List and 17 antihypertensive drugs that have an alternative relationship with the “4+7” List drugs in clinical use. Purchase volume, expenditures, and daily costs were selected as outcome variables, and were measured using Defined Daily Doses (DDDs), Chinese Yuan (CNY), and Defined Daily Drug cost (DDDc), respectively. Segmented linear regression analysis was employed to examine the change of outcome variables before and after the policy intervention.
Results: As of December 31, 2019, the completion rate of the agreed purchase volume of the 7 bid-winning antihypertensive drugs reached 173.42% in Shenzhen. After “4+7” policy, the DDDc of bid-winning antihypertensive drugs significantly decreased by 63.79% (-1.30 CNY, 95% CI= -1.43 to -1.18, p<0.001), while the DDDc of non-winning (0.28 CNY, 95% CI= 0.11 to 0.46, p<0.01) and alternative (0.14 CNY, 95% CI= 0.03 to 0.25, p<0.05) antihypertensive drugs increased markedly. The volume of bid-winning antihypertensive drugs significantly increased by 1311.76% (3.12 million DDD, 95% CI= 2.14 to 4.10, p<0.001). The overall costs of the seven “4+7” List antihypertensive drugs significantly declined by 101.34% (-5.96 million CNY, 95% CI= -7.87 to -4.04, p<0.001) after policy intervention, with an absolute reduction of 36.37 million CNY compared with the pre-“4+7” period.
Conclusion: An overall satisfying implementation effect was observed in Shenzhen. A preliminary positive policy effect of price cut and cost-saving was observed in the antihypertensive drug category. However, the DDDc of non-winning and alternative drugs increased after policy intervention, suggesting that the price monitoring and drug use management regarding NCDP policy-related drugs should be strengthened. Keywords: National Centralized Drug Procurement (NCDP); "4+7"; volume-based procurement; antihypertensive drugs; China
Effects of brief sodium fluoride treatment on the growth of early and mature cariogenic biofilms
Authors: Han Ye 
Published: June 2021

Abstract
Although fluoride has been widely used in the prevention of dental caries, the effect of fluoride on the activity of biofilm in different stages of cariogenic biofilm formation is less studied. This study aimed to investigate the antibiofilm activity of sodium fluoride during early and mature Streptococcus mutans (S. mutans) biofilms formation. S. mutans biofilms were formed on saliva-coated hydroxyapatite disks. In the early (0 ~ 46 h) and mature (46 ~ 94 h) biofilm stages, the biofilm was treated with different concentrations of fluoride (250, 500, 1000, 2000 ppm; 5 times in total, 1 min/treatment). Acidogenicity, dry weight, colony-forming units, water-soluble/insoluble extracellular polysaccharides (EPS), and intracellular polysaccharides were analyzed and confocal laser scanning microscopy images were obtained of the two stages of biofilms (early and mature biofilms). To determine the antibiofilm activity of sodium fluoride during the formation of early and mature biofilms, and to evaluate the relationship between different concentrations of sodium fluoride and antibiofilm activity. In the early cariogenic biofilm formation stage, all fluoride concentration test groups (250, 500, 1000, 2000 ppm) significantly inhibited the growth of S. mutans biofilm. The antibiofilm and anti-EPS formation activities of the brief fluoride treatment increased in a concentration-dependent pattern. At the mature biofilm stage, only the 2000 ppm fluoride treatment group significantly inhibited biofilm accumulation, activity, and intracellular/extracellular polysaccharide content compared with the control and other fluoride treatment groups. The antimicrobial activity of fluoride is related to the formation stage of cariogenic biofilm. The early formation stage of cariogenic biofilm is more susceptible to the inhibition of fluorine than the mature stage. The fluoride treatment in the early formation stage of cariogenic biofilm may be an effective means to control the development of cariogenic biofilm and prevent caries.
Predictive markers of transmission in areas with different malaria endemicity in north-eastern Tanzania based on seroprevalence of antibodies against Plasmodium falciparum
Authors: Kaaya Robert Diotrephes , Kajeguka Debora C , Matowo Johnson J , Ndaro Arnold J , Mosha Franklin W , Chilongola Jaffu O , Kavishe Reginald A 
Published: June 2021

Abstract
BackgroundDue to the scale-up of different interventions, Malaria burden declined significantly in many African countries between 2000 and 2015. As a result, some areas have become suitable for malaria elimination, and in such a situation, Due to the insensitivity of most commonly used methods, malaria transmission assessment is difficult. In north-eastern Tanzania, we tested for Plasmodium falciparum exposure by using serological markers.MethodsA cross-sectional survey was conducted in Bondo, Tanga and Hai, Kilimanjaro between June and December 2014. A total of 788 participants were enrolled and screened for malaria and IgG antibodies against PfAMA-1 and PfMSP-119 antigens using Enzyme-Linked Immuno-Sorbent Assay (ELISA). Malaria parasites were detected using polymerase chain reaction (PCR). The Mann–Whitney test was used to compare the Antibody levels between two independent groups (i.e. positive versus negative). The non-parametric Kruskal-Wallis test was used for comparisons between more than two age groups. Pearson's Chi-squared (χ2) test was used to compare proportions.ResultsGenerally, malaria prevalence by PCR in two sites was 20.4% (161), with Bondo having a higher prevalence of 28.1% (n= 154) as compared to Hai 2.9%, (n= 7), χ2=64.64, p<0.01. Anti-PfAMA-1 and anti-PfMSP-119 antibody concentrations were higher in malaria positive than malaria negative individuals, Mann-Whitney U test, p=0.07 and p=0.003 respectively. Antibody response against PfAMA-1 was significantly different between the three age groups (Kruskal-Wallis test, p<0.001).ConclusionPlasmodium falciparum exposure immunological indicators have proven useful for explaining the dynamics of transmission, especially in low transmission environments like Hai.
Occupational exposure of health care workers to blood and body fluids in West Shewa Zone, Oromia, Ethiopia, 2019: A cross-sectional study
Authors: Solomon Tesfaye , Lemessa Dejene 
Published: June 2021

Abstract
Background: Health care workers are at risk of occupational exposure to blood and body fluids even though very few studies were conducted in Ethiopia. Therefore, this study was aimed to investigate the magnitude of exposure to blood and body fluids among health care workers in governmental health facilities in West Shewa Zone, Ethiopia.Materials & Methods: A facility-based cross-sectional study was conducted in June 2018. A total of 381 health care workers were selected by simple random sampling from 31 sampled governmental health facilities using proportional to size allocation. Data were collected through self-administered questionnaires, entered into Epi-info version 7, and analyzed by SPSS version 21. Adjusted Odds Ratio (AOR) with 95% Confidence Interval (CI) computed for variables maintained in the final model of multivariable logistic regression and statistical significance declared at P<0.05.Results: A total of 377 (98.9%) health care workers participated. The study had shown that 233 (61.2%) of health care workers were exposed to blood and body fluids in their lifetime. Previous needle stick injury (AOR=0.30; 95%CI: 0.12-0.75), place of work (AOR=0.42; 95%CI: 0.26-0.68), and work experience (AOR=1.47; 95%CI: 1.13-1.93) were significantly associated factors with exposure to blood and body fluids.Conclusions: Exposures to blood and body fluids during patient care were common among health care workers in the study area. Therefore, health care workers should give due attention to their occupation's safety. Vaccination and in-service training on standard precautions should be provided and monitored for newly recruited health care workers by the health facilities.
High-speed single perceptron for optical neural networks based on microcombs
Authors: Moss David 
Published: June 2021

Abstract
Optical artificial neural networks (ONNs) — analog computing hardware tailored for machine learning [1, 2] — have significant potential for ultra-high computing speed and energy efficiency [3]. We propose a new approach to architectures for ONNs based on integrated Kerr micro-comb sources [4] that is programmable, highly scalable and capable of reaching ultra-high speeds. We experimentally demonstrate the building block of the ONN — a single neuron perceptron — by mapping synapses onto 49 wavelengths of a micro-comb to achieve a high single-unit throughput of 11.9 Giga-FLOPS at 8 bits per FLOP, corresponding to 95.2 Gbps. We test the perceptron on simple standard benchmark datasets — handwritten-digit recognition and cancer-cell detection — achieving over 90% and 85% accuracy, respectively. This performance is a direct result of the record small wavelength spacing (49GHz) for a coherent integrated microcomb source, which results in an unprecedented number of wavelengths for neuromorphic optics. Finally, we propose an approach to scaling the perceptron to a deep learning network using the same single micro-comb device and standard off-the-shelf telecommunications technology, for high-throughput operation involving full matrix multiplication for applications such as real-time massive data processing for unmanned vehicle and aircraft tracking.
State of use of Electronic Data Capture (EDC) tools in randomized controlled trials in India: results from a survey
Authors: Chakraborty Santam , Mallick Indranil , Bhattacharyya Tapesh , S Moses Arunsingh , Achari Rimpa Basu , Chatterjee Sanjoy 
Published: June 2021

Abstract
Introduction

Electronic data capture (EDC) tools can improve data quality gathered in clinical trials and may be more cost-effective than paper forms. However, limited data is available on the adoption of EDC tools in randomized controlled trials (RCT) conducted in India.
Methods

We invited investigators of registered randomized controlled trials in India to an online survey. The questionnaire included questions on the use of EDC (or alternative data capture methods) and features available. An EDC sophistication level (ranging from 1–6) was computed from the responses obtained. Respondents were also asked about barriers to the implementation of EDC in their setting. The EDC adoption rate (EAR) was defined as the proportion of clinical trials where EDC with a sophistication level of 2 or more was used. Multivariable logistic regression was used to identify factors that predicted EDC adoption.
Results

Responses were received for 400 trials, with an EAR of 27.5% (95% confidence intervals : 23.4–32.1%, n = 110). The number of sites influenced EDC adoption (odds ratio : 1.26, 95% CI : 1.12–1.47, p = 0.001) on multivariable analysis. EAR did not increase over time. The key barriers identified for not using an EDC were lack of technical support (170, 63.0%) and software cost (132, 48.9%).
Conclusion

The survey shows a low EAR in randomized trials registered in India. The barriers identified in the survey would need systematic solutions to improve the EAR in the future.
Factors Enabling Social Media: Exploring Knowledge Sharing amid student community for better academic performance
Authors: Hemalatha R. , Lavanya V. , Karthik B. 
Published: June 2021

Abstract
This paper aims to probe how the determinant influences by accessing of social media to share knowledge among the student which enhances their academic performance. The research particularly identifies in this context, the role of various components associated to knowledge sharing, and use of social media among the student’s community. Methodology – This study has adopted a Prevalence study and the data was analysed with structural equation modelling. Findings – Results approximated to adopt social media tools, which depends upon various associated components. Knowledge sharing attitudes among the student community has helped them more to share their knowledge. However, knowledge sharing approach was determined by the usefulness of knowledge. This was insusceptible from the attempt involved to improvise their academic performance. Research limitations/implications – Respondents of the survey, were done with the students from educational institution of India, cluster random sampling was used for the research. This limits the inferences made from the findings. Practicable implications – This study probes useful perceptiveness on executing social media based knowledge management by the student community. Particularly, it highlights the need to draw attention on underpinning factors, which influences knowledge sharing through social media. Originality – The study which disseminates decisive factors related to knowledge sharing with various tools of social media, thereby prompts and tests a more realistic model which may pave way for knowledge management by student community for academic performance.
The Efforts Of Sharia Micro Financial Institutions In Increasing Community Income (Case Study Of Bank Wakaf Mikro Honai Sejahtera Papua)
Authors: Yeubun Shimah Fauziah , Firdaus Muhammad Anang , Affandy Fachrudin Fiqri 
Published: June 2021

AbstractPurpose - This study aims to determine and analyze the effort of the Honai Prosperous Micro Waqf Bank in Papua in increasing community income in Heram District, Jayapura, Papua Province. Micro Waqf Bank is one of the government programs for low-scale communities.Method - This research uses a qualitative method with a case study approach. Primary data are collected from several informants who have related duties and functions such as managers, boarding school leaders, and customers from the Honai Sejahtera Micro Waqf Bank. While secondary data includes data from documents, literature, and academic studies and research. The data that has been collected is then processed and analyzed using a field analysis approach from Miles and Huberman.Result - The results of this study indicate that Honai Sejahtera Micro Waqf Bank improve the communities' income in Heram District by providing a loan for business capital using the Qardh. Besides that, the community felt the positive impact of their existence.Implication - Local Governments need to work together with LKMS to empower communities to escape poverty.Originality- This research focuses on increasing people's income through Islamic Microfinance Institution (LKMS) in Papua Province which has never been studied previously.
A Machine Learning–Based Algorithm for the Prediction of Intensive Care Unit Delirium (PRIDE): Retrospective Study
Authors: Hur Sujeong , Ko Ryoung-Eun , Yoo Junsang , Ha Juhyung , Cha Won Chul , Chung Chi Ryang 
Published: June 2021

Background
Delirium frequently occurs among patients admitted to the intensive care unit (ICU). There is limited evidence to support interventions to treat or resolve delirium in patients who have already developed delirium. Therefore, the early recognition and prevention of delirium are important in the management of critically ill patients.

Objective
This study aims to develop and validate a delirium prediction model within 24 hours of admission to the ICU using electronic health record data. The algorithm was named the Prediction of ICU Delirium (PRIDE).

Methods
This is a retrospective cohort study performed at a tertiary referral hospital with 120 ICU beds. We only included patients who were 18 years or older at the time of admission and who stayed in the medical or surgical ICU. Patients were excluded if they lacked a Confusion Assessment Method for the ICU record from the day of ICU admission or if they had a positive Confusion Assessment Method for the ICU record at the time of ICU admission. The algorithm to predict delirium was developed using patient data from the first 2 years of the study period and validated using patient data from the last 6 months. Random forest (RF), Extreme Gradient Boosting (XGBoost), deep neural network (DNN), and logistic regression (LR) were used. The algorithms were externally validated using MIMIC-III data, and the algorithm with the largest area under the receiver operating characteristics (AUROC) curve in the external data set was named the PRIDE algorithm.

Results
A total of 37,543 cases were collected. After patient exclusion, 12,409 remained as our study population, of which 3816 (30.8%) patients experienced delirium incidents during the study period. Based on the exclusion criteria, out of the 96,016 ICU admission cases in the MIMIC-III data set, 2061 cases were included, and 272 (13.2%) delirium incidents occurred. The average AUROCs and 95% CIs for internal validation were 0.916 (95% CI 0.916-0.916) for RF, 0.919 (95% CI 0.919-0.919) for XGBoost, 0.881 (95% CI 0.878-0.884) for DNN, and 0.875 (95% CI 0.875-0.875) for LR. Regarding the external validation, the best AUROC were 0.721 (95% CI 0.72-0.721) for RF, 0.697 (95% CI 0.695-0.699) for XGBoost, 0.655 (95% CI 0.654-0.657) for DNN, and 0.631 (95% CI 0.631-0.631) for LR. The Brier score of the RF model is 0.168, indicating that it is well-calibrated.

Conclusions
A machine learning approach based on electronic health record data can be used to predict delirium within 24 hours of ICU admission. RF, XGBoost, DNN, and LR models were used, and they effectively predicted delirium. However, with the potential to advise ICU physicians and prevent ICU delirium, prospective studies are required to verify the algorithm’s performance.