bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and Evaluation of an Indirect ELISA for Detection of Infection with Teladorsagia Circumcincta in Sheep
Authors: Aliabadi Jalal , Rakhshandehroo Ehsan , Yektaseresht Azadeh 
Published: April 2021

Abstract
Background

The gastrointestinal helminth, Teladorsagia circumcincta, is one of the major health risk and production-limiting disease in small ruminant populations, particularly in temperate regions. With the increasing importance of the disease management and recruited anthelminic resistant types, accurate approaches are needed for diagnosis of the infection in the host. Because of uncertain results using faecal examinations, the ELISA method was indicated for detection of the nematode antigenic materials. Despite some promising results, problems were described in terms of the test specificity and the cross-reactions. The aim of this study was therefore to evaluate worm somatic and excretory/secretory (ES) products using western blot analysis and an indirect ELISA for detecting T. circumcincta infection in sheep.
Results

Based on the immuno-reactivity analysis, immunogenic fractions with molecular weights of approximately 60, 75 and 100 kDa were detected in somatic content and two antigens of about 63 and 75 kDa in ES material. Accordingly, a specific product at 75 kDa had the strongest reaction and appeared as the most common antigenic protein. In ELISA, all sera from the infected sheep revealed the OD rates above the calculated cut-off value with about two-fold greater in average. Negative control samples were also specifically recognized with the mean OD rate of about 1/3 of the estimated cut-off value. The cross-reaction test, using rabbit hyperimmune sera, did not show reactivity with ES antigens of other prevalent nematodes include Haemonchus contortus, Protostrongylus rufescens and Marshallagia marshalli. In contrast, a strong positive reaction was found with the somatic antigens of M. marshalli.
Conclusions

The results obtained here indicates the indirect ELISA method using the ES content enables distinguishing the T. circumcincta infected sheep with high specificity. Those antigenic ES peptides with 63 and particularly 75 kDa molecular weights should be more investigated due to the potential for serological diagnostic methods and immunoprotective targets in the host.
The Direct and Indirect Effects of Clinical Empathy on Well-Being among Pre-Medical Students: A Structural Equation Model Approach
Authors: MacArthur Kelly , Stacey Clare , Harvey Sarah , Markle Jonathan 
Published: April 2021

Abstract
Background: Empathy is a well-established facet of clinical competency that research suggests is associated with enhanced medical student well-being. Since little is known about empathy and well-being before students enter medical school—during pre-medical education—the main goal of this study is to test a conceptual model of how clinical empathy is related to two indicators of well-being, depression, and burnout among pre-medical students. The theoretical model hypothesizes that three dimensions of clinical empathy—Perspective-Taking, Compassionate Care, and Standing in Patients’ Shoes— will be directly and negatively related to depression, as well as indirectly through its inverse relationship with three facets of burnout, Emotional Exhaustion, Poor Academic Efficacy, and Cynicism. Methods: Using survey data from a sample of 132 pre-medical students at an American Midwestern university, this study employs structural equation modeling (SEM) to test the theoretical model of the relationships between empathy, burnout, and depression among pre-medical students. We identify the direct effects of the three dimensions of the Jefferson Scale of Physician Empathy (JSE-S) on depression (CES-D), as well as the indirect effects of clinical empathy on depression through the three dimensions of the Maslach Burnout Inventory (MBI-S). Results: SEM analyses show that while none of the three dimensions of the JSE-S are directly related to depression, clinical empathy does significantly affect depression indirectly through burnout. Specifically, as predicted, we find that Perspective-Taking decreases Emotional Exhaustion, but, contrary to expectations, Compassionate Care increases it. And, the positive relationship between Compassionate Care and Emotional Exhaustion is particularly strong. In turn, Perspective-Taking and Compassionate Care are associated with depression in opposite directions and to different degrees. Conclusions: Findings suggest that clinical empathy as measured by the JSE-S produces both positive and negative effects on personal well-being. We conclude that further conceptual clarity of clinical empathy is needed to better discern how the different dimensions impact different indicators of well-being. Given that pre-medical education is a crucial time for emotional socialization, the challenge for medical education will be fostering the positive, cognitive aspects of clinical empathy while simultaneously mitigating the adverse effects of affective empathy on medical student well-being.
Missing Values Compensation in Duplicates Detection Using Hot Deck
Authors: Ali Abdulrazzak , Emran Nurul A. , Asmai Siti A. 
Published: April 2021

Abstract
Duplicate record is a known problem within the datasets especially within databases of huge volumes. The accuracy of duplicates detection determines the efficiency of the duplicates removal process. Unfortunately, the effort to detect duplicates becomes more challenging due to the presence of missing values within the records. This is because, during the clustering and matching process, missing values can cause records that are similar to be assigned in a wrong group, causing the duplicates left undetected. In this paper, we present how duplicates detection can be improved even though missing values are present within a data set using our Duplicates Detection within the Incomplete Data set (DDID) method. We hypothetically add the missing values to the key attributes of two datasets under study, using an arbitrary pattern to simulate both complete and incomplete data sets. We analyze the results to evaluate the performance of duplicates detection using the Hot Deck method to compensate for the missing values in the key attributes. We hypothesize that by using Hot Deck, there is a performance improvement in duplicates detection. The performance of the DDID is compared with an early duplicates detection method (called DuDe) in terms of its accuracy and speed. The findings of the experiment show that, even though the data sets are incomplete, DDID is capable to offer better accuracy and faster duplicates detection as compared to a benchmark method (called DuDe). The results of this study contribute to duplicates detection under incomplete data sets constraint.
Comparative Analysis of Streptococcus Agalactiae S03 and S07 Isolated From Schizothorax Prenanti With Different Antibiotic Resistance and Virulence
Authors: Deng Lishuang , Li Yajun , Geng Yi , Chen Defang , Ouyang Ping , Huang Xiaoli , Guo Hongrui , Zuo Zhicai , Huang Chao , Chen Zhengli , Lai Weiming , Rehman Tayyab 
Published: April 2021

Abstract
Streptococcus agalactiae (GBS), is an important Gram-positive pathogen of ﬁsh aquaculture worldwide. In this study, we performed a comparative analysis of GBS S03 and S07 isolated from Schizothorax prenanti and explored the association between phenotypic antibiotic resistance as well as virulence and the genomic characteristics. Antimicrobial sensitivity tests on 12 common antibiotics using the disc diffusion method revealed that the S03 showed resistance to seven antibiotics, while S07 showed sensitivity to the tested antibiotics. Pathogenicity analysis demonstrated greater virulence of S07 than S03. Then, the occurrence of antibiotic resistance and virulence genes was identified using whole-genome sequence (WGS) of S03 and S07. There were mefE, tetO, lnuB, lsaE, APH3', and sat-4 resistance genes present only in S03 genome. And just S03 had gyrA and parC genes mutations. In addition to 51 virulence genes in both S03 and S07 genomes, S07 additionally carried virulence genes associated with invasion, such as SAN_1519, rfbA and cylE genes. There was complete concordance between genotypic evidence and phenotypic characteristics. Virulence factors and phylogenetic analysis showed that S03 and human sources shared an extremely close evolutionary relationship. Our findings provide important proof for using WGS as an effective tool of phenotypic predictions of GBS.
Standardization of electrolyte leakage data and a novel liquid nitrogen control improve measurements of cold hardiness in woody tissue
Authors: Kovaleski Alisson Pacheco , Grossman Jake J 
Published: April 2021

Abstract
Background. A variety of basic and applied research programs in plant biology require the accurate and reliable determination of plant tissue cold hardiness. Over the past 50 years, the electrolyte leakage method has emerged as a popular and practical method for quantifying the amount of damage inflicted on plant tissue by exposure to freezing temperatures. Numerous approaches for carrying out this method and analyzing the resultant data have emerged. These include multiple systems for standardizing and modeling raw electrolyte leakage data and multiple protocols for boiling samples in order to maximize leakage as a positive control. We compare four different routines for standardization of leakage data and assess a novel control method - immersion in liquid nitrogen in lieu of traditional boiling – and apply them to woody twigs collected from 12 maple (Acer) species in early spring. We compare leakage data from these samples using each of four previously published forms of data analysis and boiling vs. liquid nitrogen controls and validate each of these approaches against visual estimates of freezing damage and differential thermal analysis. Results. Through presentation of our own data and re-analysis of previously published findings, we show that standardization of raw data against estimates of both minimum and maximum attainable freezing damage allows for reliable estimation of cold hardiness at the species level and across studies in diverse systems. Furthermore, use of our novel liquid nitrogen control produces data commensurate across studies and enhances the consistency and realism of the electrolyte leakage method, especially for very cold hardy samples. Conclusion. Future leakage studies that relativize data against minimum and maximum leakage and that employ our updated liquid nitrogen control will contribute generalizable, repeatable, and realistic data to the existing body of cold hardiness research in woody plants. Data from studies conducted using a liquid nitrogen (and not a boiling) control can still be compared to previously published data, especially when raw data are standardized using the best-performing approach among those we assessed. Electrolyte leakage of woody twigs emerges as a useful technique for quickly assessing the probability of tissue death in response to freezing in dormant plants. Differential thermal analysis may provide different and complementary information on cold hardiness.
Fungal Deterioration of the Bagasse Storage from the Harvested Sugarcane
Authors: Peng Na , Yao Ziting , Wang Ziting , Huang Jiangfeng , Khan Muhammad Tahir , Chen Baoshan , Zhang Muqing 
Published: April 2021

Abstract
Background

Sugarcane is an essential crop for sugar and ethanol production. Immediate processing of sugarcane is necessary after harvesting because of rapid sucrose losses and deterioration of stalks. This study was conducted to fill the knowledge gap regarding the exploration of fungal communities in harvested deteriorating sugarcane. Experiments were performed on simulating production at 30 ℃ and 40 ℃ after 0, 12, and 60 hours (h) of sugarcane harvesting and powder-processing.
Results

Both pH and sugar content declined significantly within 12 h. Fungal taxa were unraveled using ITS amplicon sequencing. With the increasing temperature, the diversity of the fungal community decreased over time. The fungal community structure significantly changed within 12 h of bagasse storage. Before storing, the dominant genus (species) in bagasse was Wickerhamomyces (W. anomalus). Following storage, at 30 ℃ and 40°C, Kazachstania (K. humilis) and Saccharomyces (S. cerevisiae) gradually grew, becoming abundant fungi. We found that the bagasse at different temperatures had a similar pattern after storage for the same intervals, indicating that the temperature was the primary cause for the variation of core features. Moreover, the impact of dominant fungal species on sugar content and pH of stored sugarcane juice was investigated. Also, the correlation between top fungal genera and significant environmental factors was assessed.
Conclusions

The study highlighted the importance of timeliness to refine sugar as soon as possible after harvesting the sugarcane crop. The lessons learned from this research are vital for sugarcane growers and the sugar industry for minimizing postharvest losses.
Subsidence Prediction of Overburden Strata and Ground Surface in Shallow Coal Seam Mining
Authors: Cao Jian , Huang Qingxiang , Guo Lingfei 
Published: April 2021

Abstract
Shallow coal seam with thick soil layer is widely reserved in the Jurassic Coalfield, Western China, mining-induced subsidence represents complex characteristics. Combining with physical simulation, theoretical analysis and in-situ observation, the overburden strata structure in dip direction were revealed, and the subsidence prediction models were established, based on this, the subsidence equations of overburden strata and ground surface were proposed. The results show that after shallow coal seam mining, based on the subsidence and movement characteristics, the overburden strata structure can be divided into three zones, which are "boundary pillar F-shape zone" (BPZ), "trapezoid goaf zone" (TGZ) and "coal pillar inverted trapezoidal zone" (CPZ). The subsidence of overburden strata depends on the key stratum, while the subsidence of soil layer depends on the bedrock subsidence basin, which is between the bedrock and thick soil layer. The bedrock subsidence is mainly related to mining height and bulking coefficient in TGZ, while it is mainly affected by mining height and distribution load on the key stratum in BPZ and CPZ. According to physical simulation and theoretical model, the maximum surface subsidence of No.1–2 seam mining in Ningtiaota coal mine are 1.1m and 1.07m respectively, which is basically consistence with the result of in-situ observation (1.2m).
Synthesis and Characterization of CaTiO3-LnAlO3(Ln=La, Nd) Ceramics Manufactured by Reaction Sintering Method
Authors: Zhou Shicheng , Wu Qiang , Xu Hanrui , Luan Xiaowen , Hu Sang , Zhou Xianjie , He Sen , Wang Xi , Zhang Hailin , Chen Xiuli , Zhou Huanfu 
Published: April 2021

Abstract
CaTiO3-LnAlO3(Ln = La, Nd) ceramics were manufactured by reaction-sintering for produce low cost and high efficiency materials. Using reaction-sintering method to manufacture these ceramics, which have excellent comprehensive properties. The subtle variations on densification behavior, phase transformation, phase composition, microstructure evolution and performances of CaTiO3-LnAlO3(Ln = La, Nd) ceramics were studied systematically. The XRD pattern indicates that the Ca0.61La0.39Al0.39Ti0.61O3 phase and Ca0.7Nd0.3Ti0.7Al0.3O3 phase were generated under certain environmental conditions respectively. The ceramics exhibited excellent performance parameters: when εr is 42.03(45 635), the quality factor is 45500GHz (45 635) In addition, even in the environment of large temperature changes the ceramics can still maintain good performance. In conclusion, the reaction sintering method is an economic, convenient, available preparation means of making the CaTiO3-LnAlO3(Ln = La, Nd) ceramics and has broad prospects of application and development.
Flood Early Warning Systems using Machine Learning Techniques. Application to a Catchment located in the Tropical Andes of Ecuador.
Authors: Muñoz Paul , Orellana-Alvear Johanna , Bendix Jörg , Célleri Rolando 
Published: April 2021

Abstract
Short-rain floods, especially flash-floods, produce devastating impacts on society, the economy, and ecosystems. A key countermeasure is to develop Flood Early Warning Systems (FEWSs) aimed at forecasting flood warnings with sufficient lead time for decision making. Although Machine Learning (ML) techniques have gained popularity among hydrologists, the research question poorly answered is what is the best ML technique for flood forecasting? To answer this, we compare the efficiencies of FEWSs developed with the five most common ML techniques for flood forecasting, and for lead times between 1 to 12 hours. We use the Tomebamba catchment in the Ecuadorean Andes as a case study, with three warning classes to forecast No-alert, Pre-alert, and Alert of floods. For all lead times, the Multi-Layer Perceptron (MLP) technique achieves the highest model performances (f1-macro score) followed by Logistic Regression (LR), from 0.82 (1-hour) to 0.46 (12-hour). This ranking was confirmed by the log-loss scores, ranging from 0.09 (1-hour) to 0.20 (12-hour) for the above mentioned methods. Model performances decreased for the remaining ML techniques (K-Nearest Neighbors, Naive Bayes and Random Forest) but their ranking was highly variable and not conclusive. Moreover, according to the g-mean, LR models depict greater stability for correctly classifying all flood classes, whereas MLP models are specialized in the minority (Pre-alert and Alert) classes. To improve the performance and the applicability of FEWSs, we recommend future efforts to enhance input data representation and to develop communication applications between FEWSs and the public as tools to boost the preparedness of the society against floods.
Clinical Effectiveness of Treatment of Children Afflicted by Lumbar Tuberculosis With Posterior-only Approach Using Poly-ether-ether-ketone Cage Combined With Single-segment Instrumentation
Authors: Xu Zhengquan , Chen Lanhua , Wang Changsheng , Zhang Liqun , Xu Weihong 
Published: April 2021

Abstract
Background: We sought to investigate the clinical outcomes of posterior-only approach using poly-ether-ether-ketone (PEEK) cage combined with single-segment instrumentation in the treatment of lumbar tuberculosis in children.Methods: Between February 2008 and August 2017 in our hospital, 18 children with single-segment lumbar tuberculosis were enrolled in this study. Children were treated by a posterior-only approach using PEEK cage combined with single-segment instrumentation. Medical records and radiographs were retrospectively analyzed. Visual analogue scores (VAS) were used to evaluate measures of quality of daily life. Criteria defined from the American Spinal Injury Association (ASIA) were used to evaluate measures of neurological function.Results: Mean follow-up time was 54.6 ± 12.1 months (39–84 months). No severe complications were noted to have occurred. Measures indicated there was satisfactory bone fusion for observations for all patients. Mean Cobb angles were significantly decreased from the mean preoperative angle (19.8° ± 13.1°) to those both postoperatively (-4.9° ± 7.6°) and at final follow-up (-3.5° ± 7.3°) (both P < 0.05), with a mean angle loss of 1.7° ± 0.9°. Th erythrocyte sedimentation rate (ESR) returned to normal levels for all patients within 3 months postoperatively. All patients had significant postoperative improvement in respect to neurological performance and VAS scores.Conclusions: The posterior-only approach using PEEK cage combined with single-segment instrumentation was found to be an effective and feasible treatment option for children with lumbar tuberculosis. Such procedures can likely be used to help patients by facilitating reconstruction of spinal stability, and increasing retainment of lumbar mobility in conjunction with reduced invasiveness compared to counterpart treatments.
A novel nomogram to predict 90-day mortality of patients with sepsis
Authors: Zeng Qingbo , He Long-Ping , Zhang Nianqing , Lin Qin-Wei , Zhong lin-Cui , Song Jing-Chun 
Published: April 2021

Abstract
Background

Sepsis is a prevalent disease among intensive care units and continues to be a frequent cause of death. This study aimed to establish a nomogram for mortality prediction in patients with sepsis.
Methods

We carried out a retrospective, single-center study based on 231 patients with sepsis and data was collected from May 2018 to October 2020. Patients were randomly split into training and validation cohorts. In the training cohort, multivariate logistic regression analysis and a stepwise algorithm were performed to identify risk factors, which were presented with a predictive nomogram. The receiver operating characteristic (ROC), calibration plots and decision curve analysis (DCA) were used to estimate the performance of the nomogram in both the training and validation cohorts.
Results

A total of 231 patients with sepsis were enrolled in the study, and the 90-day mortality was 31.6%. There were 161 and 70 cases in training and validation cohorts respectively. Statistical analyses showed that Age, international normalized ratio (INR), lactate (Lac), and thrombomodulin (TM) were the risk factors for 90-day mortality. The area under the curve was 0.810 (95% CI, 0.739 to 0.881) in training cohort and 0.813(95% CI, 0.708 to 0.917) in the validation cohort. Calibration curve showed good performance of this nomogram. Decision curve analysis demonstrated that the nomogram was clinical utility.
Conclusion

This nomogram offering a probability of mortality for a given patient can benefit outcome improvement and clinicians in making clinical decision.
Genetic Diversity and Population Structure Analysis of Grass pea (Lathyrus Sativus L.) Accessions Collected from North-Western Ethiopia Using SSR Markers
Authors: Abebe Desalegn , Abraham Adane , Oselebe Happiness , Afiukwa Celestine , Ilesanmi Oluyinka , Abebe Tiegist Dejene 
Published: April 2021

Abstract
Grass pea ( Lathyrus sativus L.) is a legume crop known to be an excellent source of protein, tolerant to drought, waterlogging, and salinity. The crop is used as an alternative source of protein to reduce malnutrition for resource-poor people and farmers leaving in marginal areas. However, due to the presence of a neurotoxin that causes lathyrism in the crop, it has been neglected and underutilized. As a necessary first step towards, therefore, this investigation was undertaken to assess the genetic diversity and population structure that existed within grass pea accessions collected from the North-Western part of Ethiopia using simple sequence repeat markers. Twenty-five grass pea accessions collected from the Ethiopian Biodiversity Institute were planted at the College of Agricultural Science, Ebonyi State University, Nigeria. The genomic DNA was extracted using Quick-DNA™ ZR Plant/Seed Miniprep Kit and amplified by ABI Veriti PCR with 10 pairs of SSR markers in IITA, Ibadan, Nigeria. Out of 10 SSR primers, only eight primers were polymorphic. A total of 41 alleles were detected with an average of 5.13. The Polymorphic information content and gene diversity values ranged from 0.074 to 0.944 with a mean of 0.474 and 0.536 respectively. The largest pairwise genetic distance (0.365) was detected between North Gondar and East Gojam populations. The ФPT (analogs of FST test) estimated through AMOVA were 0.24, 0.20, and 0.05 for within accessions, among regions, and population within regions respectively. The highest genetic differentiation value (76%) resides within accessions followed by 20% among regions. Both population structure and cluster analysis grouped the 25 grass pea accessions into two distinctive subgroups. This grouping pattern indicates the presence of gene flow among geographic regions. In general, the findings of this study indicate that despite few numbers of SSR markers it was possible to detect genetic diversity among grass pea accessions indicating the power of the SSR marker in picking up the existing genetic diversity within the studied accessions.