bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative transcriptomic and metabolomic analysis reveals pectoralis highland adaptation across altitudinal songbirds
Authors: xiong ying , Hao Yan , Cheng Yalin , Fan Liqing , Song Gang , Li Dongming , Qu Yanhua , Lei Fumin 
Published: January 2020

Abstract
Background Pectoralis phenotypic variation plays a fundamental role in locomotion and thermogenesis in highland birds. However, its regulatory and metabolic mechanisms remain enigmatic to date. Here, we integrated phenomic, transcriptomic and metabolomic approaches to determine muscle variation and its underpinning mechanisms across altitudinal songbirds. Results Phenomics revealed that all highland birds had considerable increases in muscle oxidative capacity, capillarity, and mitochondrial abundance. Correspondingly, transcriptomic analyses found that differentially expressed genes in modules associated with phenotypes enriched in blood vessel, muscle structure development, and mitochondrial organization. Despite similar traits and functional enrichments across highland birds, different mechanisms drove their occurrence in part for their own various evolutionary histories. Importantly, a metabolic feature shared by highland birds is the improvement in insulin sensitivity and glucose utilization through activating insulin signaling pathway, which is vital to increase muscle oxidative capacity and maintain metabolic homeostasis. Nevertheless, fatty acid biosynthesis and oxidation are enhanced in species with a long evolutionary history, also differing from ketone body metabolism in recently introduced colonizer. Conclusions Our study represents a vital contribution to reveal the regulatory and metabolic basis of pectoralis variation across altitudinal songbirds.
Temporal dynamics of the gut microbiome and metabolome in preterm and term infants from birth through the first year of life
Authors: Yap Polly Soo Xi , Chong Chun Wie , Kamar Azanna Ahmad , Yap Ivan Kok Seng , Choo Yao Mun , Lai Nai Ming , Teh Cindy Shuan Ju 
Published: January 2020

Abstract
Background: Emerging evidence has shown a link between the perturbations and development of the gut microbiota in infants to their immediate and long-term health. In comparison to the healthy full-term neonate, preterm neonates experience disparate gut bacterial establishment (e.g. duration in the womb), colonisation (e.g. mode of delivery), and development (e.g. frequent use of antibiotics). To better understand the assembly of the gut microbiota in preterm infants, faecal samples were longitudinally collected from preterm (n = 19) and term (n = 20) infants, up to 12 months after birth. We characterised bacterial compositions by 16S rRNA gene sequencing (n = 141) and metabolomics profiling (n = 141) using nuclear magnetic resonance (NMR) spectroscopy.Results: Significant differences in faecal bacterial composition between term and preterm infants were detected in sample collected in week 2, month 6 and month 12. Interestingly, separation of the bacterial composition between term and preterm infants was more pronounced at month 12 as compared to the earlier time-points, suggesting distinct level of microbial maturation in gut between the two groups. Intestinal microbiota of preterm neonates was consistently characterised by dominance of pathogenic bacteria from the Enterobacteriaceae family and a paucity of strictly anaerobic taxa including Veillonella and Bacteroides relative to infants born at term. Consistent result was observed in the stool NMR spectroscopy in which clear separation in stool metabolomics profiles was observed between the term and preterm neonates.Conclusion: Overall, we identified a panel of amino acid metabolites and central metabolism intermediates in the preterm infants’ stool, possibly indicating incomplete fermentation of complex polysaccharides in the guts of these infants. In contrast, the term infant stool had significantly higher levels of metabolites which are commonly found in milk such as fucose and β-hydroxybutyrate (BHBA). Birth weight was selected as the best explanatory variable for the metabolomics profiles, pointing to the strong relationship between protein synthesis, as well as fucose and BHBA in physical development. By following both term and preterm infants for 12 months, our study reported the dynamic of gut microbial composition and their contribution to metabolism and potential impact to growth in neonates.
Combined and interaction effect of Chlamydia pneumoniae infection and smoking on lung cancer: a case-control study in southeast China
Authors: Xu Xin , Liu Zhiqiang , Xiong Weimin , Qiu Minglian , Kang Shuling , Xu Qiuping , Cai Lin , He Fei 
Published: January 2020

Abstract
Objective: This case-control study investigated the role of Chlamydia pneumoniae (Cpn) infection in the pathogenesis of lung cancer and the combined and interaction effect of Chlamydia pneumoniae infection and smoking or other environmental factors.Methods: The study was comprised of 449 lung cancer patients and 512 age- and gender-matched healthy controls. All participants provided a 5-ml fasting peripheral venous blood sample for testing Cpn-specific IgG and IgA by using micro-immunofluorescence. Besides analyzing the associations between Cpn and lung cancer, combined effect analysis, logistic regression, and the excel table made by Andersson were used to analyze the combined and interaction effects of Cpn and environmental factors on lung cancer.Results: Compared to those with no evidence of serum Cpn IgA or Cpn IgG, those with both Cpn IgG+ and IgA+ had 2.00 times the risk (95% CI: 1.34 - 3.00) of developing lung cancer. Smokers with Cpn IgG+ or IgA+ were associated with a significantly increased risk of lung cancer, the adjusted OR was 1.79 (95% CI: 1.10-2.91) or 2.27(95% CI:1.38-3.72), respectively. Those exposed to passive smoking with Cpn IgG+ or IgA+ also increased the risk of lung cancer, the adjusted OR was 1.82 (95% CI: 1.20-2.77) or 1.87(95% CI:1.22-2.87), respectively. The similar results were also observed among alcohol drinking people. Multiplicative and additive interactions were not observed between Cpn infection and environmental factors. The combined effects of Cpn IgG+ or IgA+ and smoking, passive smoking, family history of cancer were found on lung cancer.Conclusion: The Cpn infection was potentially associated with primary lung cancer in the Chinese Han population and had combined effects with smoking, passive smoking, and the family history of cancer.
Stacked genetically modified soybean harboring herbicide resistance and insecticide rCry1Ac shows strong defense and redox homeostasis disturbance after glyphosate application
Authors: Zanatta Caroline Bedin , Benevenuto Rafael Fonseca , Nodari Rubens Onofre , Agapito-Tenfen Sarah Zanon 
Published: January 2020

Abstract
BackgroundWorld agricultural production of genetically modified (GM) products in particular, the combination of different traits/genes in the same plant has been intense over the last decade. The stacking of herbicide and insect-resistant transgenic genes can result in fitness costs that rely on the type and strength of the selection pressure exerted by the environment. Here we report the results of transcriptomic analysis comparing the effect of glyphosate on various biological processes, metabolic pathways, and main shikimic enzymes in stacked versus single soybean resistant varieties.ResultsGene expression data were grouped according to treatment, ie the herbicidal factor strongly influenced. Common physiological results between the single and established varieties were mainly in Redox metabolism, energy, and metabolism. Photosynthesis was only found negatively affected in the single variety. The defense components, although present in both varieties, show a more intense presence in staked pathways, that demonstrated pathways related to up-regulated secondary metabolites biosynthesis, a known response when plants are under various stress conditions. RT-PCR results confirmed that native EPSPS expression was up-regulated at the same level for single and stacked events. However, metabolic differences in expression were observed, suggesting a distinct cascade effect between simple and stacked, triggered by glyphosate application.ConclusionChanges in plant metabolism by glyphosate application have been observed in several pathways, particularly the shiquimate pathway, suggesting that event staking may promote a more intense defensive genetic response. Omics profiling techniques, such as transcriptome, can be considered tools to support risk assessment based on detecting unwanted effects, both on plant physiological changes and on the safety of foods and products from new genetic editing technologies.
The Influence of Income on Medical School Admissions in Canada: A Retrospective Cohort Study
Authors: Pitre Tyler , Thomas Alexander , Evans Kyle , Jones Aaron , Mountjoy Margo , Costa Andrew P. 
Published: January 2020

Abstract
BACKGROUND. The socioeconomic status of applicants to Canadian medical schools has been understudied in the past two decades. Institutional efforts have been made to address the lack of socioeconomic diversity across Canada during this time. We investigated the income characteristics of medical school applicants, as well as the relationship between applicant income and offer of admission, to characterize the current state of socioeconomic diversity in medical admissions.METHODS. We conducted a retrospective cohort study on 26,120 applicants at one Ontario medical school from 2013 to 2018. Characteristics of applicants who were offered admission were compared to the general population and applicants not offered admission. Regression analyses were used to investigate the association between median total neighborhood income and successful admission, as well as performance on admission testing criteria, including: the MMI, CASPer, GPA, and the MCAT.RESULTS. The median total neighborhood income for medical school applicants was $98,816, which was approximately $28,480 higher than the Canadian general population. Those not admitted to the medical school had a median total neighborhood income of $98,304 compared to $105,984 for those offered admission (p<0.001). This trend was seen in every province and territory in Canada. Median total neighborhood income was an independent predictor of admission; applicants in the >75 th percentile income group had 54% increased odds of being offered admission when compared to applicants in the <25 th percentile. Performance on the MCAT, MMI and CASPer were moderately associated with income; applicants’ GPAs were not associated with income.CONCLUSION. Medical school applicants are from higher economic strata compared to the general population. Despite already representing a high economic stratum, a higher median total neighborhood income relative to other applicants was associated with an offer of admission.
Extensively Drug Resistant Acinetobacter baumannii ST369 Infection in Emergency Intensive Care Unit in Shandong Province, China
Authors: Jiang Meijie , Li Lin , Liu Shuang , Zhang Zhijun , Li Ning , Zhao Shuping 
Published: January 2020

Abstract
Background: Acinetobacter baumannii is a significant nosocomial infectious pathogen worldwide. The aim of this study is to characterize the molecular epidemiology of Acinetobacter baumannii isolated from the clinical infection, providing the epidemiology data for prevention and control. Four patients hospitalized in EICU on January 31st, 2014, and then Acinetobacter baumannii infection was observed. Antimicrobial resistance and resistance genes were analyzed by antimicrobial susceptibility testing and PCR sequencing. Pulse field gel electrophoresis (PFGE) and multilocus sequence typing (MLST) were used to analyze these strains’ clonal relatedness. Results: Sixteen strains were recovered, of which 4 strains were isolated from 4 patients, and others were from environment in EICU, such as air, phone and ventilator. All strains belonged to clonal pulsotype A and ST369. Sixteen antibiotics were used to perform the susceptibility testing, and all strains were extensively drug resistant (XDR) Acinetobacter baumannii, they were only susceptible to tigecycline and polymyxin B, but resistant to others, including carbapenems and aminoglycoside antibiotics. Furthermore, all strains carried blaOXA-23-like carbapenemases gene with ISAba1 insertion sequence in the upstream, aminoglycoside resistance genes ant(3″)-I, 16S rRNA methylase gene armA and disinfectant resistant gene qacE△1, which were mainly responsible for the spread of antimicrobial resistance. Fortunately, enhanced control measures were immediately implemented after this infection, and new strains were no longer detected for consecutive three months. Conclusions: molecular epidemiology of blaOXA-23-like carbapenemase-producing Acinetobacter baumannii ST369 in EICU of a hospital was characterized. Routine monitoring should be strengthen to prevent outbreaks of this disease.
Delta Neutrophil Index (DNI) as a Predictive and Prognostic factor for Candidemia patients: Matched Case-Control study
Authors: Park So Yeon , LEE JIN SEO , Oh Jihyu , Park Ji-Young 
Published: January 2020

Abstract
Background: Delayed antifungal therapy for candidemia leads to increased mortality. Discriminating bacterial infection from candidemia in systemic inflammatory response syndrome (SIRS) patients is very complex and difficult. Delta Neutrophil Index (DNI) is recently considered as a new factor which can distinguish infections from non-infections and reflect the severity of sepsis. We aimed to assess whether DNI can predict and provide a prognosis for candidemia in SIRS patients.Methods: A matched case-control study was conducted from July 2016 to June 2017 at Kangdong Sacred Heart Hospital. Among patients with comorbidity of SIRS, those with candidemia were classified as the case group, while those with negative blood culture results were classified as the control group. The matching conditions included age, blood culture date, and SIRS onset location. To evaluate DNI as a predictive and prognostic factor for candidemia, multivariate logistic regression was performed.Results: The 140 included patients were assigned to each group in a 1:1 ratio. DNI-D1 values measured on the blood culture date were higher in the case group ( p <0.001). In the multivariate analyses, DNI_D1 (Odds ration〔ORs〕2.138, 95% confidential interval 〔CI〕1.421-3.217, P <0.001) and Candida colonization were confirmed as predictive factors for candidemia. The cutoff value of DNI for predicting candidemia was 2.75%. The area under the curve for DNI value was 0.804 (95% CI, 0.719-0.890, p<0.001), with a sensitivity and specificity of 72.9% and 78.6%, respectively. Analysis of 14-day mortality was conducted for patients with candidemia. DNI_D1 and DNI_48, measured 2 days after the onset of candidemia, were both significantly high in the non-survivor group.Conclusion: DNI was identified to be a predictive factor for candidemia in patients wit SIRS and a prognostic factor that predicts 14-day mortality in candidemia patients. DNI, along with clinical characteristics of patients, were useful in determining the occurrence of candidemia in patients with SIRS.
Identification of Bio-climatic Determinants and Potential Risk Areas for Kyasanur Forest Disease in Southern India using MaxEnt Modelling Approach
Authors: Pramanik Malay Kumar , Singh Poonam , Dhiman Ramesh C 
Published: January 2020

Abstract
Background: Kyasanur Forest Disease (KFD), known as monkey fever was for the first time reported in 1957 from Shivamogga district of Karnataka. But since 2011, it is spreading to the neighbouring state of Kerala, Goa, Maharashtra, and Tamil Nadu. The disease is transmitted to humans, monkeys and by the infected bite of ticks Haemaphysalis spinigera. It is known that deforestation and ecological changes are the main reasons for KFD emergence, but the bio-climatic understanding and emerging pathways remain unknown.Methods: The present study aims to understand the bio-climatic determinants of KFD tick distribution in southern India using Maximum Entropy (MaxEnt) model. The analysis was done using 34 locations of Haemaphysalis spinigera occurrence and nineteen bio-climatic variables from WorldClim. Climatic variables’ contribution was assessed using the jackknife test and mean AUC 0.859 which indicated the model performs with very high accuracy.Results: Most influential variables affecting the spatial distribution of Haemaphysalis spinigera were the average temperature of the warmest quarter (bio10, contributed 32.5%), average diurnal temperature range (bio2, contributed 21%), precipitation of wettest period (bio13, contributed 17.6%), and annual precipitation (bio12, contributed 11.1%). The highest probability of Haemaphysalis spinigera presence was found when mean warmest quarter temperature ranged between 25.4-30°C. The risk of availability of the tick increases noticeably when the mean diurnal temperature ranged between 8-10°C. The tick also preferred habitat having an annual mean temperature (bio1) between 23-26.2°C, mean temperature of the driest quarter (bio9) between 20-28°C, and mean temperature of the wettest quarter (bio8) between 22.5-25°C.Conclusions: The results have established the relationship between bioclimatic variables and KFD tick distribution and mapped the potential areas for KFD in adjacent areas wherein surveillance for the disease is warranted for early preparedness before the occurrence of outbreaks etc. The modelling approach has been found a very useful tool to link bioclimatic variables with present and predicted distribution of Haemaphysalis spinigera tick .
Awareness, treatment, and control of hypertension and related factors in adult Iranian Population
Authors: Mirzaei Mohsen , Mirzaei Masoud , Bagheri-Fahraji Behnam , Dehghani Ali 
Published: January 2020

Abstract
Background Hypertension, known as the silent killer, is a major risk factor for cardiovascular disease. This study aims to estimate awared, treated, and controlled hypertensive and relevant predictors in an adult Iranian population. Methods This cross-sectional study was conducted on 10000 adults aged 20-69 years in Yazd, Iran. They were selected through multi-stage random cluster sampling in 2015-2016.Blood pressure was measured three-time with standard protocol by trained health workers. Those with a positive history of hypertension and using anti-hypertensive drugs, prescribed by a physician, were considered hypertensive. Hypertension was defined as systolic blood pressure ≥140 mmHg and/or diastolic BP of ≥90 mmHg. Uncontrolled hypertension was defined in accordance with recommended treatment targets by the Joint National Committee (JNC7). Logistic regression was used to assess the predictors of hypertension awareness, treatment and control. Results The prevalence of hypertension was 37.3%, and the prevalence of pre-hypertension was 46.4%. 49.7% of People with hypertension were aware of their disease, and 71.5% of them were using antihypertensive drugs prescribed by physicians. Blood pressure was controlled in 38.9% of the treated patients. In the adjusted model, older age, female sex, and history of diabetes mellitus were positively associated with higher awareness. High physical activity, tobacco smoking, and diabetes are the only predictors of treated high blood pressure. Younger age, female sex, and higher education were determinants of controlled hypertension. Having health insurance was significantly correlated with awareness and control of hypertension. Conclusion Hypertension is a public health problem in this population, which is not well controlled. Half of the patients were unaware. Intervention for increased screening coverage is needed. It should plan to raise public awareness about hypertension and improve hypertension control under supervision of physicians. Implement a family physician program is recommended in the health system.
Real-time forecast of influenza outbreak using dynamic network marker based on minimum spanning tree
Authors: Yang Kun , Xie Jialiu , Xie Rong , Pan Yucong , Liu Rui , Chen Pei 
Published: January 2020

Abstract
Background: The influenza pandemic is a wide-ranging threat to people’s health and property all over the world. Developing effective strategies for predicting the influenza outbreak which may prevent or at least get ready for a new influenza pandemic is now a top global public health priority.Methods: Owing to the complexity of influenza outbreaks that are usually involved with spatial and temporal characteristics of both biological and social systems, however, it is a challenging task to achieve the real-time monitoring of influenza outbreaks. In this study, by exploring the rich dynamical information of the city network during influenza outbreaks, we developed a computational method, the minimum-spanning-tree-based dynamical network marker (MST-DNM), to identify the tipping point or critical stage prior to the influenza outbreak.Results: With historical records of influenza outpatients between 2009 and 2018, the MST-DNM strategy has been validated by accurate predictions of the influenza outbreaks in three Japanese cities/regions respectively, i.e., Tokyo, Osaka, Hokkaido. These successful applications show that the early-warning signal was detected 4 weeks on average ahead of each influenza outbreak.Conclusion: The results show that our method is of considerable potential in the practice of public health surveillance.
Exponential Synchronization for Fractional-order Time-delayed Memristive Neural Networks
Authors: Dawei Ding , Yaqin Zhang , Nian Wang 
Published: January 2020

Abstract
Considering the fact that the exponential synchronization of neural networks has been widely used in theoretical research and practical application of many scientific fields, and there are a few researches about the exponential synchronization of fractional-order memristor-based neural networks (FMNN). This paper concentrates on the FMNN with time-varying delays and investigates its exponential synchronization. A simple linear error feedback controller is applied to compel the response system to synchronize with the drive system. Combining the theories of differential inclusions and set valued maps, a new sufficient condition concerning exponential synchronization is obtained based on comparison principle rather than the traditional Lyapunov theory. The obtained results extend exponential synchronization of integer-order system to fractional-order memristor-based neural networks with time-varying delays. Finally, some numerical examples are used to demonstrate the effectiveness and correctness of the main results.
Multi Antenna Precoding Algorithm Based on M Spread Spectrum
Authors: Ruihua Sun , Junying Bai , Yongli An 
Published: January 2020

Abstract
MIMO multi antenna technology can increase the capacity and channel utilization of the communication system without increasing the bandwidth, and become the key technology in the new generation of mobile communication system. However, each channel has its own channel parameters, so in the process of signal transmission, the influence of channel parameters should be considered. When the signal is received, it needs to be restored, which leads to the complexity of the receiving signal. Therefore, this paper proposes a multi antenna precoding algorithm based on M spread spectrum, precoding before sending signal spread spectrum to simplify the signal receiving equipment, and verify the feasibility of the algorithm through system error rate.