bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional and Clinical Significance of Ror1 in Lung Adenocarcinoma
Authors: Schiavone Giovanna , Samantha Epistolio , Vittoria Martin , Francesca Molinari , Jessica Barizzi , Luca Mazzucchelli , Milo Frattini , Wannesson Luciano 
Published: January 2021

Abstract
BACKGROUND:Receptor tyrosine kinase-like orphan receptor 1 (ROR1) is normally detectable in embryonic tissues and absent in adult tissues. ROR1 was shown to inhibit apoptosis, potentiate EGFR signaling and reported to be overexpressed and associated with poor prognosis in several tumor models. This study aimed to assess the expression of ROR1 in lung adenocarcinoma (AC) patients. METHODS: We analyzed ROR1 expression by quantitative real-time PCR (qRT-PCR) in 56 histologically confirmed lung AC, stage I to IV, in addition we evaluated its association with TTF-1 (thyroid transcription factor-1) expression and the main molecular alterations involved in lung cancerogenesis. RESULTS: ROR1 overexpression was observed in 28.6% of the entire cohort, using a cut-off of 1, or in 51.8% of the cases using the median value as threshold. Among patients without any genetic alteration, ROR1 overexpression was observed in 34.8% considering a cut-off of 1 and 52.2% considering the median value. The distribution of ROR1 was homogeneous among the different molecular categories: we found no association of ROR1 expression and the presence of gene mutations/rearrangements or the expression of TTF-1. CONCLUSIONS: ROR1 overexpression could constitute a potential therapeutic target because altered in a consistent number of lung AC, especially in cases without druggable genetic alterations. ROR1 expression is independent of classical lung cancer molecular alterations and not correlated, in a Caucasian cohort, to TTF-1 expression.
DV-DVFS: Merging Data Variety and DVFS Technique to Manage the Energy Consumption of Big Data Processing
Authors: Ahmadvand Hossein , Foroutan Fouzhan , Fathy Mahmood 
Published: January 2021

Abstract
Data variety is one of the most important features of Big Data. Data variety is the result of aggregating data from multiple sources and uneven distribution of data. This feature of Big Data causes high variation in the consumption of processing resources such as CPU consumption. This issue has been overlooked from previous work. To overcome the mentioned problem, in the present work, we used Dynamic Voltage and Frequency Scaling (DVFS) to reduce the energy consumption of computation. To this goal, we consider two types of deadlines as our constraint. Before applying the DVFS technique to computer nodes, we estimate the processing time and the frequency needed to meet the deadline. In the evaluation phase, we have used a set of data sets and applications. The experimental results show that our proposed approach surpasses the other scenarios in processing real datasets. Based on the experimental results in this paper, DV-DVFS can achieve up to 15% improvement in energy consumption.
Are preventive measures adequate? An evaluation of the implementation of COVID-19 prevention and control measures in nursing homes in China
Authors: Shi Meihong , Zhang Fengying , He Xinxin , Huang Siyuan , Zhang MingFeng , Hu Xiuying 
Published: January 2021

Abstract
Background: The novel coronavirus disease 2019 (COVID-19) pandemic has become a challenge for nursing homes in China. Nursing homes are particularly dangerous places regarding the spread of COVID-19 given that they house vulnerable, high-risk populations. As such, several useful guidelines for coping with COVID-19 in nursing homes have been provided. However, the actual implementation rates of such guidelines are unknown. This study aims to document the adherence of nursing homes to the Ministry of Civil Affairs guidelines for COVID-19 prevention and control in nursing homes.Methods: A cross-sectional study was conducted among 484 nursing homes in 136 cities of 28 provinces in China. A self-report questionnaire was created based on the Ministry of Civil Affairs guidelines for COVID-19 prevention and control in nursing homes (first edition). The questionnaire and the Transformational Leadership in the Public Sector Scale were sent to nursing home managers via the Wenjuanxing app online from February 7 to 29, 2020. A total of 461 responses were included in the analysis. Results: The average overall implementation rate of COVID-19 prevention and control measures was 80.0% (143.97/180). The average implementation rates for hygienic behaviour management, access management were lower, with 75.3% and 78.7% respectively. The number of medical staff, established a quarantine unit (room), leadership’s three dimensions included intellectual stimulation, individualized consideration, and idealized influence were found to affect the prevention and control implementation (p<0.05). Nursing homes that did not have hospital-nursing home cooperation, did not have medical staff, and had not established a quarantine unit (room) had low implementation rates (p<0.01). 69.8% (332/461) of nursing home managers reported they had serious resource problems, inadequate of protective supplies (72.0%) and staff shortage (47.7%) were two primary problems. Conclusion: Overall, the implementation of prevention and control measures by nursing homes are insufficient during the epidemic in China. Further education for staff, provide support to staff, supply adequate protective resources, and cooperation with hospitals are required to improve the implementation rate. It is urgent for nursing homes keep the safety of the residents and staff.
Synthesis of oxadiazole-2-oxide derivatives as potential drug candidates for schistosomiasis targeted on SjTGR
Authors: Li Gongming , Guo Qingqing , Feng Chao , Chen Huan , Zhao Wenjiao , Li Shu , Hong Yang , sun dequn 
Published: January 2021

Abstract
Background: Schistosomiasis is a chronic parasitic disease that affects millions of people’s health worldwide. Since the increasing drug-resistant to praziquantel (PZQ), which is the primary drug for schistosomiasis, developing new drugs to treat schistosomiasis is crucial. Oxadiazole-2-oxides have been identified as a potential anti-schistosomiasis reagent targeted to thioredoxin glutathione reductase (TGR). Methods: In this work, one of the oxadiazole-2-oxides derivatives furoxan was used as the lead compound to exploit series of novel furoxan derivatives for studying inhibitory activity against both recombinant Schistosoma japonicum TGR containing selenium (rSjTGR-Sec) and soluble worm antigen protein (SWAP) containing wild type Schistosoma japonicum TGR (wtSjTGR) to develop new leading compound for schistosomiasis. Thirty nine novel derivatives were prepared to test their activity to both two enzymes. The docking method was used to detect the bind sites between active molecule and SjTGR; The structure-activity relationship (SAR) of these novel furoxan derivatives was preliminarily analyzed. Results: It was founded that several new derivatives such as compounds 6a-6d, 9ab, 9bd, 9be have a better activity to rSjTGR-Sec or SWAP containing wtSjTGR than furoxan. Interestingly, all intermediates bearing hydroxy (6a-6d) showed excellent inhibitory activity to both two enzymes. In particular, compound 6d with trifluoromethyl on pyridine ring has been found to have much higher inhibition to both rSjTGR-Sec (half-maximal inhibitory concentration, IC50,7.5nM) and SWAP containing wtSjTGR (IC50 55.8nM) than furoxan. Additionally, the docking method revealed the matching sites between 6d and Schistosoma japonicumi TGR (SjTGR), which theoretically lends support to the inhibitory activity of 6d. Conclusion: The data obtained herein showed preliminarily that 6d with trifluoromethyl on pyridine ring could be a valuable leading compound for further study.
Evaluating the Effects of Electronic Health Records System Adoption on the Performance of Malaysian Health Care Providers
Authors: Salleh Mohd Idzwan Mohd , Abdullah Rosni , Zakaria Nasriah 
Published: January 2021

Abstract
Background: The Ministry of Health of Malaysia has invested significant resources to implement an electronic health record (EHR) system to ensure the full automation of hospitals for coordinated care delivery. Thus, evaluating whether the system has been effectively utilized is necessary, particularly regarding how it predicts the post-implementation primary care providers’ performance impact. Methods: Convenience sampling was employed for data collection in three government hospitals for seven months. A standardized efficacy survey for EHR systems was administered to primary health care providers (specialists, medical officers, and nurses) as they participated in medical education programs. Empirical data were assessed by employing partial least squares-structural equation modeling for hypothesis testing.Results: The results demonstrated that knowledge quality had the highest score for predicting performance and had a large effect size, whereas system compatibility was the strongest component of system quality. The findings indicated that EHR systems supported the clinical tasks and workflows of care providers, which increased system quality, whereas increased quality of knowledge improved user performance. Conclusion: Given these findings, knowledge quality and effective use should be incorporated into the evaluation of EHR system efficacy in health institutions. Data mining features can be integrated into current systems for easily and systematically generating health populations and disease trend analysis, improving clinical knowledge of care providers and aiding in maintaining their productivity. The validated survey instrument can be further tested with empirical surveys in other public and private hospitals with different interoperable EHR systems.
Multicenter evaluation of EIAs and CLIAs in the detection of hepatitis C virus antibody among blood donors in China
Authors: Chang Le , Ji Huimin , Guo Fei , Jiang Xinyi , Wang Lunan 
Published: January 2021

Abstract
Background: Recent data on anti-HCV screening assays among large population of blood donors is limited. The present study aimed to perform a multicenter evaluation of EIAs and CLIAs for detection of anti-HCV among blood donors in 16 different Chinese blood establishments.Methods: A total of 1,309 samples including 582 anti-HCV screening negatives and 727 positives collected from 15 blood establishments all over China. Ten different anti-HCV assays (eight EIAs and two CLIAs) were evaluated in 16 different blood centers/banks. Confirmatory testing was performed using recombinant immunoblot assay and HCV RNA tests.Results: The plasma panel contained 963 negative samples, 261 positives, and 85 indeterminate samples, based on the results of confirmatory test. False positive rate of screening tests was 39.67% (382/963) and the positive prediction value was only 35.76% (260/727). Among ten anti-HCV assays, Roche and InTec had the highest sensitivity (98.47%), while KHB and Wantai (indirect) had the highest specificity (99.23%). Then we analyzed the combined performance of these assays with two assays’ strategy widely used in China: Ortho or Abbott together with InTec could find all the true positives and Wantai (indirect) with Livzon (sandwich) got a highest specificity of 97.80%. Indeterminate samples showed quite different signal to cutoff (S/CO) ratios tested by Roche compared with confirmed positives (4.84 vs 19.36, p<0.0001), and higher S/CO ratios than confirmed negatives (4.84 vs 2.94, p=0.020). Conclusion: False reactivity in anti-HCV screening should be treated as urgent issue. RIBA indeterminate donations may be a special group, while it still worth to be further studied.
Generation of UCiPSCs-derived neurospheres for cell therapy and its application
Authors: Li Shuai , Zhao Huifang , Han Xiaobo , Bin Ni , He Lang , Mukama Omar , Habimana Jean de Dieu , Lin Zuoxian , Huang Rongqi , Huang Hualin , Tian Chao , Tang Feng , Li Zhiyuan 
Published: January 2021

Abstract
Background Neural stem cells（NSCs）therapy remains one of the most potential approaches for the treatment of neurological disorders. The discovery of human induced pluripotent stem cells (hiPSCs) and the establishment of hiPSC-derived human neural stem cells (hiNSCs) have revolutionized the technique of cell therapy. Meanwhile, it is often required that NSCs are stored and transported to a long distance for research or treatment purposes. Although high survival rates could be maintained, conventional methods for cell transportation (dry ice or liquid nitrogen) are inconvenient and expensive. Therefore，the establishment of a safe, affordable, and low-cost strategy to store and transport easily accessible hiPSCs and hiNSCs, with characteristics that match fetal hNSCs, is incredibly urgent.Methods We reprogrammed human urinary cells to iPSCs using a non-integrating, virus-free technique and differentiated the iPSCs toward iNSCs/neurospheres and neurons, under Good Manufacturing Practice (GMP)-compatible conditions. The pluripotency of iPSCs and iNSCs was characterized by a series of classical methods (surface markers, karyotype analysis and in vitro as well as in vivo differentiation capabilities, etc).Results Here, our results showed that we successfully generated hiNSCs/neurospheres from more available, non-invasive, and more acceptable urinary cells by a virus-free technique. Next, we demonstrated that the iNSCs differentiated into mature cerebral cortical neurons and neural networks. Interestingly, hiNSCs survived longer as neurospheres at ambient temperature (AT) than those cultured in a monolayer. Within 7 days approximately, the neural viability remained at > 80%, while hiNSCs cultured in a monolayer died almost immediately. Neurospheres exposed to AT that were placed under standard culture conditions (37 ℃, 5% CO2) recovered their typical morphology, and retained their proliferation and differentiation abilities. Conclusions In this study, we provided a simple method for the storage of NSCs as neurospheres at AT as an alternative method to more costly and inconvenient traditional methods of cryopreservation. This will enable hiNSCs to be transported over long distances at AT and facilitate the therapeutic application of NSCs as neurospheres without any further treatment.
Iterative Guided Machine Learning-Assisted Systematic Literature Reviews: A Diabetes Case Study
Authors: Zimmerman John , Soler Robin , James Lavinder , Sarah Murphy , Charisma Atkins , LaShonda Hulbert , Richard Lusk , Peng Ng Boon 
Published: January 2021

Abstract
Background: Systematic Reviews (SR), studies of studies, use a formal process to evaluate the quality of scientific literature and determine ensuing effectiveness from qualifying articles to establish consensus findings around a hypothesis. Their value is increasing as the conduct and publication of research and evaluation has expanded and the process of identifying key insights becomes more time consuming. Text analytics and Machine Learning (ML) techniques may help overcome this problem of scale while still maintaining the level of rigor expected of SRs.Methods: In this article, we discuss an approach that uses existing examples of SRs to build and test a method for assisting the SR title and abstract pre-screening by reducing the initial pool of potential articles down to articles that meet inclusion criteria. Our approach differs from previous approaches to using ML as a SR tool in that it incorporates ML configurations guided by previously conducted SRs, and human confirmation on ML predictions of relevant articles during multiple iterative reviews on smaller tranches of citations. We applied the tailored method to a new SR review effort to validate performance. Results: the case study test of the approach proved a sensitivity (recall) in finding relevant articles during down selection that may rival many traditional processes. Conclusions: We believe this iterative method can help overcome bias in initial ML model training by having humans reinforce ML models with new and relevant information, and is an applied step towards transfer learning for ML in SR.
The NeST (Neoadjuvant Systemic Therapy in Breast Cancer) Study: National Practice Questionnaire of United Kingdom Multi-Disciplinary Decision Making&nbsp;
Authors: Whitehead Ian , Irwin Gareth , Bannon Finian , Coles Charlotte , Copson Ellen , Cutress Ramsey , Dave Rajiv , Gardiner Matthew , Grayson Margaret , Holcombe Chris , Irshad Sheeba , O'Brien Ciara , O'Connell Rachel , Palmieri Carlo , Shaaban Abeer , Sharma Nisha , Singh Jagdeep , Potter Shelley , McIntosh Stuart 
Published: January 2021

Abstract
Background: Neoadjuvant systemic therapy (NST) is increasingly used in the treatment of breast cancer, yet it is clear that there is significant geographical variation in its use in the UK. This study aimed to examine stated practice across UK breast units, in terms of indications for use, radiological monitoring, pathological reporting of treatment response, and post-treatment surgical management. Methods: Multidisciplinary teams (MDTs) from all UK breast units were invited to participate in the NeST study. A detailed questionnaire assessing current stated practice was distributed to all participating units in December 2017 and data collated securely usingREDCap. Descriptive statistics were calculated for each questionnaire item.Results: Thirty-nine MDTs from a diverse range of hospitals responded. All MDTs routinely offered neoadjuvant chemotherapy (NACT) to a median of 10% (range 5-60%) of patients. Neoadjuvant endocrine therapy (NET) was offered to a median of 4% (range 0-25%) of patients by 66% of MDTs. The principal indication given for use of neoadjuvant therapy was for surgical downstaging. There was no consensus on methods of radiological monitoring of response, and a wide variety of pathological reporting systems were used to assess tumour response. Twenty-five percent of centres reported resecting the original tumour footprint, irrespective of clinical/radiological response. Radiologically negative axillae at diagnosis routinely had post-NACT or post-NET sentinel lymph node biopsy (SLNB) in 73.0% and 84% of centres respectively, whereas 16% performed SLNB pre-NACT. Positive axillae at diagnosis would receive axillary node clearance at 60% of centres, regardless of response to NACT.Discussion: There is wide variation in the stated use of neoadjuvant systemic therapy across the UK, with general low usage of NET. Surgical downstaging remains the most common indication of the use of NAC, although not all centres leverage the benefits of NAC for de-escalating surgery to the breast and/or axilla. There is a need for agreed multidisciplinary guidance for optimising selection and management of patients for NST. These findings will be corroborated in phase II of the NeST study which is a national collaborative prospective audit of NST utilisation and clinical outcomes.
The burden of the current curative expenditure of injury in Dalian,China—A study based on the “System of Health Accounts 2011”
Authors: Sun Shu , Yang Liuna , Hu Xinzhu , Zhu Yalan , Liu Boxi , Yang Yunbin , Wang Xin 
Published: January 2021

Abstract
Background: Injury is one of the major public health problems and causes more than 5 million deaths in the world annually. Cases of specific types of injury are life-threatening and heavily-burdened to individuals and society. This study was aimed to assess the financial burden of injury on patients. Methods: A total of 565 medical institutions were selected with multistage stratified cluster random sampling, containing 152553 valid samples. Subsequently, the distribution of injury current curative expenditure (CCE) in different dimensions (including age and site of injury) was analyzed under the framework of System of Health Accounts 2011 (SHA 2011) using the established database. Results: In China, both urban and rural injury mortality rates showed an upward trend of more than 5 percentage points from 2006 to 2016. In Dalian, the CCE of injury reached 1572.73 million RMB, accounting for 7.45% of the total CCE. Those aged 15-24 reported larger proportion of CCE than the other age groups. As for the injuries in body parts, injuries occurred to the spine, lower limb, head and foreign body cost most.Conclusions: Dalian has a relatively serious burden of injury costs. The essential and primary goal is to reduce the cost. Young people should pay attention to protect their head and limbs from injury, and related government sectors should implement preventive and educative measures.
Artificial Intelligence-Based Nomogram for Small-Incision Lenticule Extraction
Authors: Park Seungbin , Kim Hannah , Kim Laehyun , Kim Jin-kuk , Lee In Sik , Ryu Ik Hee , Kim Youngjun 
Published: January 2021

Abstract
Background: Small-incision lenticule extraction (SMILE) is a surgical procedure for the refractive correction of myopia and astigmatism, which has been reported as safe and effective. However, over- and under-correction still occur after SMILE. The necessity of nomograms is emphasized to achieve optimal refractive results. Ophthalmologists diagnose nomograms by analyzing the preoperative refractive data with their individual knowledge which they accumulate over years of experience. Our aim was to predict the nomograms of sphere, cylinder, and astigmatism axis for SMILE accurately by applying machine learning algorithm.Methods: We retrospectively analyzed the data of 3,034 eyes composed of four categorical features and 28 numerical features selected from 46 features. The multiple linear regression, decision tree, AdaBoost, XGBoost, and multi-layer perceptron were employed in developing the nomogram models for sphere, cylinder, and astigmatism axis. The scores of the root mean square error (RMSE) and accuracy were evaluated and compared. Subsequently, the feature importance of the best models was calculated.Results: AdaBoost achieved the highest performance with an RMSE of 0.1378, 0.1166, and 5.17 for the sphere, cylinder, and astigmatism axis, respectively. The accuracies of which error below 0.25 D for the sphere and cylinder nomograms and 25° for the astigmatism axis nomograms were 0.969, 0.976, and 0.994, respectively. The feature with the highest importance was pre-operative manifest refraction for all the cases of nomograms. For the sphere and cylinder nomograms, the following highly important feature was the surgeon.Conclusions: Among the diverse machine learning algorithms, AdaBoost exhibited the highest performance in prediction of the sphere, cylinder, and astigmatism axis nomograms for SMILE. The study proved the feasibility of applying artificial intelligence (AI) to nomograms for SMILE. Also it may enhance the quality of the surgical result of SMILE by providing assistance in nomograms and preventing the misdiagnosis in nomograms.
Molecular characteristics of rotavirus genotypes circulating in the south of Benin, 2016-2018
Authors: Agbla Jijoho Michel , Esona Mathew D , Agbankpé Alidéhou Jerrold , Capo-Chichi Annick , Gautam Rashi , Dougnon Tamègnon Victorien , Razack Osseni , Bowen Michael D , Bankolé Honoré Sourou 
Published: January 2021

Abstract
ObjectiveRotavirus remains the main causative agent of gastroenteritis in young children in countries that have not yet introduced the vaccine. In Benin, rotavirus vaccine was introduced late December 2019 into the EPI. This study aims to provide pre-vaccination era rotavirus genotyping data in Benin. These data can supplement data from the surveillance system of Ministry of Health of Benin which is supported by the World Health Organization (WHO).ResultsOf the 420 diarrheal stool samples, actively collected in southern Benin from July 2016 through November 2018 from children under five years old and suffering from gastroenteritis, 167 (39.8%) samples were rotavirus EIA positive. 186 (44.3%) samples contained amplifiable rotavirus RNA detected by qRT-PCR method and were genotyped using one-step RT-PCR multiplex genotyping method. G1P[8] represents the predominant genotype (32%) followed by the G2P[4] (26%), G3P[6] (16%), G12P[8] (13%) and mixed G and P types (1%). Four samples (2%) could not be assigned both G and P type speciﬁcity.