bluuebunny/crossref_metadata_2025_split huggingface dataset:
Label free proteomics and systematic analysis of secretome reveals effector candidates regulated by SGE1 and FTF1 in the plant pathogen Fusarium oxysporum f. sp. cubense tropical race 4
Authors: Zhao Shixue , An Bang , Guo Yanhua , Hou Xingrong , Luo Hongli , He Chaozu , Wang Qiannan 
Published: April 2020

Abstract
Background
Phytopathogens secreted effectors during host colonization to suppress or trigger plant immunity. Identification of new effectors is one of the research focuses in recent years. There is only a limited knowledge about effectors of Fusarium oxysporum f. sp. Cubense tropical race 4 (Foc TR4), the causal agent of wilt disease in Cavendish banana.

Results
Two transcription factors, SGE1 and FTF1, were constitutively over-expressed in Foc TR4 to partially mimic the in-planta state. Secreted proteins with high purity were prepared through a two-round extraction method. Then the secretome were analyzed via label free proteomics method. A total of 919 non-redundant proteins were detected, of which 74 proteins were predicted to be effector candidates. Among these candidates, 29 were up-regulated and 13 down-regulated in the strain over-expressing SGE1 and FTF1, 8 were up-regulated and 4 down-regulated in either SGE1 or FTF1 over expression strain.

Conclusions
Through label free proteomics analysis, a series of effector candidates were identified in secretome of Foc TR4. Our work put a foundation for functional research of these effectors.
Transcriptomic and metabolomic analyses reveal mechanisms of adaptation to salinity in which carbon and nitrogen metabolism is altered in sugar beet roots
Authors: Liu Lei , Wang Bin , Liu Dan , Zou Chunlei , Wu Peiran , Wang Ziyang , Wang Yubo , Li Caifeng 
Published: April 2020

AbstractBackgroundBeta vulgarisL. is one of the main sugar-producing crop species and is highly adaptable to saline soil. This study explored the alterations to the carbon and nitrogen metabolism mechanisms enabling the roots of sugar beet seedlings to adapt to salinity.ResultsThe ionome, metabolome, and transcriptome of the roots of sugar beet seedlings were evaluated after 1 day (short term) and 7 days (long term) of 300 mM Na+treatment. Salt stress caused reactive oxygen species (ROS) damage and ion toxicity in the roots. Interestingly, under salt stress, the increase in the Na+/K+ratio compared to the control ratio on day 7 was lower than that on day 1 in the roots. The transcriptomic results showed that a large number of differentially expressed genes (DEGs) were enriched in various metabolic pathways. A total of 1279 and 903 DEGs were identified on days 1 and 7, respectively, and were mapped mainly to 10 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Most of the genes were involved in carbon metabolism and amino acid (AA) biosynthesis. Furthermore, metabolomic analysis revealed that sucrose metabolism and the activity of the tricarboxylic acid (TCA) cycle increased in response to salt stress. After 1 day of stress, the content of sucrose decreased, whereas the content of organic acids (OAs) such as L-malic acid and 2-oxoglutaric acid increased. After 7 days of salt stress, nitrogen-containing metabolites such as AAs, betaine, melatonin, and (S)-2-aminobutyric acid increased significantly. In addition, multiomic analysis revealed that the expression of the gene encoding xanthine dehydrogenase (XDH) was upregulated and that the expression of the gene encoding allantoinase (ALN) was significantly downregulated, resulting in a large accumulation of allantoin. Correlation analysis revealed that most genes were significantly related to only allantoin and xanthosine.ConclusionsOur study demonstrated that carbon and nitrogen metabolism was altered in the roots of sugar beet plants under salt stress. Nitrogen metabolism plays a major role in the late stages of salt stress. Allantoin, which is involved in the purine metabolic pathway, may be a key regulator of sugar beet salt tolerance.
Evaluation of the effectiveness of high-risk human papilloma self-sampling test for cervical cancer screening in Bolivia
Authors: Allende Gustavo , Surriabre Pedro , Ovando Neli , Calle Pamela , Torrico Andrea , Villarroel Jaime , Bossens Michel , Fontaine Véronique , Rodriguez Patricia 
Published: April 2020

Abstract
Background
In Bolivia the incidence and mortality rates of uterine cervix cancer are the highest in America. The main factor contributing to this situation is the difficulty of establishing and maintaining quality prevention programs based on cytology. We aimed to evaluate the effectiveness of HR-HPV testing on self-collected samples to detect cervical intra-epithelial neoplasia and identify the best combination of screening tests.

Methods
A total of 469 women, divided in two groups, were included in this study. The first group included 362 women that underwent three consecutively primary screening tests: self-collected sampling for HR-HPV detection, conventional cervical cytology and visual inspection under acetic acid (VIA). The second group included 107 women referred with a positive HR-HPV test that underwent conventional cervical cytology and VIA. The presence of high grade intraepithelial lesion (CIN 2+) or invasive cancer was verified by colposcopy and biopsy.

Result
In the screening group the sensitivity to detect high grade intraepithelial lesion (CIN 2+) or invasive cancer were 100, 76, 44% for the VIA, HR-HPV test and cytology, respectively. In the referred group, the sensitivity to detect high grade intraepithelial lesion (CIN 2+) or invasive cancer by VIA and cytology were 100 and 81%, respectively.

Conclusions
VIA and HR-HPV self-sampling were the best combination to detect CIN2+ lesions. Cytology analysis gave the poorest performance.
Prevalence of neonatal hypothermia and its associated factors in East Africa: a systematic review and meta-analysis
Authors: Beletew Biruk , Mengesha Ayelign , Wudu Mesfin , Abate Melese 
Published: April 2020

Abstract
Background
Neonatal hypothermia is a global health problem and a major factor for neonatal morbidity and mortality, especially in low and middle-income countries. Therefore, this systematic review and meta-analysis aimed to assess the prevalence of neonatal hypothermia and its associated factors in Eastern Africa.

Methods
We used the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines to search electronic databases (PubMed, Cochrane Library and Google Scholar; date of last search: 15 October 2019) for studies reporting the prevalence and associated factors of neonatal hypothermia. The data was extracted in the excel sheet considering prevalence, and categories of associated factors reported. A weighted inverse variance random-effects model was used to estimate the magnitude and the effect size of factors associated with hypothermia. The subgroup analysis was done by country, year of publication, and study design.

Results
A total of 12 potential studies with 20,911 participants were used for the analysis. The pooled prevalence of neonatal hypothermia in East Africa was found to be 57.2% (95%CI; 39.5–75.0). Delay in initiation of breastfeeding (adjusted Odds Ratio(aOR) = 2.83; 95% CI: 1.40–4.26), having neonatal health problem (aOR = 2.68; 95% CI: 1.21–4.15), being low birth weight (aOR =2.16; 95%CI: 1.03–3.29), being preterm(aOR = 4.01; 95%CI: 3.02–5.00), and nighttime delivery (aOR = 4.01; 95% CI:3.02–5.00) were identified associated factors which significantly raises the risk of neonatal hypothermia.

Conclusions
The prevalence of neonatal hypothermia in Eastern Africa remains high. Delay in initiation of breastfeeding, having a neonatal health problem, being low birth weight, preterm, and nighttime delivery were identified associated factors that significantly raises the risk of neonatal hypothermia.
Comparison of serum protein profiles between major depressive disorder and bipolar disorder
Authors: Rhee Sang Jin , Han Dohyun , Lee Yunna , Kim Hyeyoung , Lee Junhee , Lee Kangeun , Shin Hyunsuk , Kim Hyeyoon , Lee Tae Young , Kim Minah , Kim Se Hyun , Ahn Yong Min , Kwon Jun Soo , Ha Kyooseob 
Published: April 2020

Abstract
Background
Major depressive disorder and bipolar disorder are prevalent and debilitating psychiatric disorders that are difficult to distinguish, as their diagnosis is based on behavioural observations and subjective symptoms. Quantitative protein profile analysis might help to objectively distinguish between these disorders and increase our understanding of their pathophysiology. Thus, this study was conducted to compare the peripheral protein profiles between the two disorders.

Methods
Serum samples were collected from 18 subjects with major depressive disorder and 15 subjects with bipolar disorder. After depleting abundant proteins, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and label-free quantification were performed. Data-dependent acquisition data were statistically analysed from the samples of 15 subjects with major depressive disorder and 10 subjects with bipolar disorder who were psychotropic drug-free. Two-sided t-tests were performed for pairwise comparisons of proteomes to detect differentially-expressed proteins (DEPs). Ingenuity Pathway Analysis of canonical pathways, disease and functions, and protein networks based on these DEPs was further conducted.

Results
Fourteen DEPs were significant between subjects with major depressive disorder and those with bipolar disorder. Ras-related protein Rab-7a (t = 5.975, p = 4.3 × 10− 6) and Rho-associated protein kinase 2 (t = 4.782, p = 8.0 × 10− 5) were significantly overexpressed in subjects with major depressive disorder and Exportin-7 (t = -4.520, p = 1.5 × 10− 4) was significantly overexpressed in subjects with bipolar disorder after considering multiple comparisons. Bioinformatics analysis showed that cellular functions and inflammation/immune pathways were significantly different.

Conclusions
Ras-related protein Rab-7a, Rho-associated protein kinase 2, and Exportin-7 were identified as potential peripheral protein candidates to distinguish major depressive disorder and bipolar disorder. Further large sample studies with longitudinal designs and validation processes are warranted.
Are we doing enough? Improved breastfeeding practices at 14 weeks but challenges of non-initiation and early cessation of breastfeeding remain: findings of two consecutive cross-sectional surveys in KwaZulu-Natal, South Africa
Authors: Horwood C. , Haskins L. , Engebretsen I. , Connolly C. , Coutsoudis A. , Spies L. 
Published: April 2020

Abstract
Background
KwaZulu-Natal (KZN) Initiative for breastfeeding support (KIBS) was a multipronged intervention to support the initiation and sustaining of breastfeeding, implemented between 2014 and 2017. We present results of two surveys conducted before and after KIBS implementation to assess changes in infant feeding practices in KZN over this time period.

Methods
Two cross-sectional surveys were conducted in primary health care clinics. Multistage stratified random sampling was used to select clinics and participants. Sample size was calculated to provide district estimates of 14-week exclusive breastfeeding (EBF) rates at baseline (KIBS1), and provincial estimates at endpoint (KIBS2). At KIBS1 the sample required was nine participating clinics in each of 11 districts (99 clinics) with 369 participants per district (N = 4059), and at KIBS2 was 30 clinics in KZN with 30 participants per clinic (N = 900). All caregivers aged ≥15 years attending the clinic with infants aged 13- < 16 weeks were eligible to participate. Data was collected using structured interviews on android devices. Multi-variable logistic regression was used to adjust odds ratios for differences between time points.

Results
At KIBS1 (May2014- March2015), 4172 interviews were conducted with carers, of whom 3659 (87.6%) were mothers. At KIBS2 (January–August 2017), 929 interviews were conducted which included 788 (84.8%) mothers. Among all carers the proportion exclusively breastfeeding was 44.6 and 50.5% (p = 0.1) at KIBS1 and KIBS2 respectively, but greater improvements in EBF were shown among mothers (49.9 vs 59.1: p = 0.02). There were reductions in mixed breastfeeding among all infants (23.2% vs 16.3%; p = 0.016). Although there was no change in the proportion of carers who reported not breastfeeding (31.9% vs 32.8%; p = 0.2), the duration of breastfeeding among mothers who had stopped breastfeeding was longer at KIBS2 compared to KIBS1 (p = 0.0015). Mothers who had returned to work or school were less likely to be breastfeeding (adjusted odds ratio [AOR] 3.76; 95% CI 3.1–4.6), as were HIV positive mothers (AOR 2.1; 95% CI 1.7–2.6).

Conclusion
Despite improvements to exclusive breastfeeding, failure to initiate and sustain breastfeeding is a challenge to achieving optimal breastfeeding practices. Interventions are required to address these challenges and support breastfeeding particularly among working mothers and HIV positive mothers.
Effect of metastatic site on survival in patients with neuroendocrine neoplasms (NENs). An analysis of SEER data from 2010 to 2014
Authors: Trikalinos Nikolaos A. , Tan Benjamin R. , Amin Manik , Liu Jingxia , Govindan Ramaswamy , Morgensztern Daniel 
Published: April 2020

Abstract
Background
Neuroendocrine neoplasms (NENs) display variable behaviors based on origin and grade. We assumed that both tumor origin and the location of metastasis may play a role in survival.

Methods
We queried the SEER database (2010–2014) for patients with an established diagnosis of NENs and documented site of metastasis and identified 2005 patients. Overall survival (OS) at the time points were estimated by the Kaplan-Meier method Cox proportional-hazards models were used to evaluate the relationship of the interested variables and OS.

Results
Lung, liver, bone and brain metastases were observed in 9, 77, 7 and 6% of metastatic patients respectively. In the multivariate model, metastasis locations were significantly associated with worse survival (liver HR: 1.677 (1.226–2.294); (bone metastasis HR: 1.412 (0.965–2.065); brain HR: 1.666 (1.177–2.357)). We produced a scoring system based on site of origin, metastasis location, age, gender, histology and tumor size that can stratify metastatic NEN patients in low, intermediate and high-risk categories to help physicians with decision making.

Conclusion
Site of metastasis plays an important role in survival of metastatic NEN patients independent of commonly described prognostic factors and should be considered in survival estimates.
Prevalence and determinants of modern contraceptive utilization among rural lactating mothers: findings from the primary health care project in two northwest Ethiopian districts
Authors: Derso Terefe , Biks Gashaw Andargie , Yitayal Mezgebu , Ayele Tadesse Awoke , Alemu Kassahun , Demissie Getu Debalkie , Wolde Haileab Fekadu , Dellie Endalkachew , Azale Telake , Misganaw Bisrat , Kebede Adane , Fetene Destaw , Gebremdhin Tsegaye , Atnafu Asmamaw 
Published: April 2020

Abstract
Background
Contraceptive utilization is a guarantee to avert unwanted pregnancies. In Ethiopia however, more than half of the rural women have shorter birth intervals. Consequently, 17 and 8% of the births have been either mistimed (wanted at later date) or unwanted, respectively. Therefore, this study investigated modern contraceptive utilization and its predictors among rural lactating women.

Methods
A community based-cross-sectional study was conducted from May 01 to June 29, 2019, in Dabat and Gondar zuria districts, northwest Ethiopia. Data from 603 lactating mother were collected through face to face interviews using a structured questionnaire. Bivariate and multivariate logistic regression analyses were fitted to identify the independent predictors of modern contraceptive utilization.

Results
The overall prevalence of modern contraceptive (MC) utilization rate was 45.8% [95% CI: 38.01, 53.59]. The contraceptive method mix was dominated by Depo-Provera (39.8%) followed by implants (4.8%). The odds of utilization of contraceptive were 5.58 times higher among mothers of children with fully immunized [AOR = 5.58, 95% CI: 3.45, 9.01] compared to mothers whose children were vaccinated partially or not at all. Mothers who received antenatal [AOR = 1.74, 95% CI: 1.13, 4.43] and postnatal care [AOR = 2.02, 95%CI: 1.24, 2.91) were 1.74 and 2.02 folds more likely to utilize modern contraceptives than mothers who did not receive such care, respectively.

Conclusion
The prevalence of modern contraceptive utilization in this study area was lower than the planed national target. In the region, child immunization service is one of the promising platforms for reaching lactating mothers with modern contraceptive utilization. Our findings suggest that antenatal and postnatal care visits are the other key determinants of modern contraceptive utilization. Thus, in low-resource settings like ours, the health system approaches to improved antenatal and, postnatal care and child immunization services should be intensified with more effective advice on modern contraceptive utilization to reduce unwanted pregnancies.
The long-term health effects of attending a selective school: a natural experiment
Authors: Butler Jessica , Black Corri , Craig Peter , Dibben Chris , Dundas Ruth , Hilton Boon Michelle , Johnston Marjorie , Popham Frank 
Published: April 2020

Abstract
Background
Education is widely associated with better physical and mental health, but isolating its causal effect is difficult because education is linked with many socioeconomic advantages. One way to isolate education’s effect is to consider environments where similar students are assigned to different educational experiences based on objective criteria. Here we measure the health effects of assignment to selective schooling based on test score, a widely debated educational policy.

Methods
In 1960s Britain, children were assigned to secondary schools via a test taken at age 11. We used regression discontinuity analysis to measure health differences in 5039 people who were separated into selective and non-selective schools this way. We measured selective schooling’s effect on six outcomes: mid-life self-reports of health, mental health, and life limitation due to health, as well as chronic disease burden derived from hospital records in mid-life and later life, and the likelihood of dying prematurely. The analysis plan was accepted as a registered report while we were blind to the health outcome data.

Results
Effect estimates for selective schooling were as follows: self-reported health, 0.1 worse on a 4-point scale (95%CI − 0.2 to 0); mental health, 0.2 worse on a 16-point scale (− 0.5 to 0.1); likelihood of life limitation due to health, 5 percentage points higher (− 1 to 10); mid-life chronic disease diagnoses, 3 fewer/100 people (− 9 to + 4); late-life chronic disease diagnoses, 9 more/100 people (− 3 to + 20); and risk of dying before age 60, no difference (− 2 to 3 percentage points). Extensive sensitivity analyses gave estimates consistent with these results. In summary, effects ranged from 0.10–0.15 standard deviations worse for self-reported health, and from 0.02 standard deviations better to 0.07 worse for records-derived health. However, they were too imprecise to allow the conclusion that selective schooling was detrimental.

Conclusions
We found that people who attended selective secondary school had more advantaged economic backgrounds, higher IQs, higher likelihood of getting a university degree, and better health. However, we did not find that selective schooling itself improved health. This lack of a positive influence of selective secondary schooling on health was consistent despite varying a wide range of model assumptions.
Convolutional neural network models for cancer type prediction based on gene expression
Authors: Mostavi Milad , Chiu Yu-Chiao , Huang Yufei , Chen Yidong 
Published: April 2020

Abstract
Background
Precise prediction of cancer types is vital for cancer diagnosis and therapy. Through a predictive model, important cancer marker genes can be inferred. Several studies have attempted to build machine learning models for this task however none has taken into consideration the effects of tissue of origin that can potentially bias the identification of cancer markers.

Results
In this paper, we introduced several Convolutional Neural Network (CNN) models that take unstructured gene expression inputs to classify tumor and non-tumor samples into their designated cancer types or as normal. Based on different designs of gene embeddings and convolution schemes, we implemented three CNN models: 1D-CNN, 2D-Vanilla-CNN, and 2D-Hybrid-CNN. The models were trained and tested on gene expression profiles from combined 10,340 samples of 33 cancer types and 713 matched normal tissues of The Cancer Genome Atlas (TCGA). Our models achieved excellent prediction accuracies (93.9–95.0%) among 34 classes (33 cancers and normal). Furthermore, we interpreted one of the models, 1D-CNN model, with a guided saliency technique and identified a total of 2090 cancer markers (108 per class on average). The concordance of differential expression of these markers between the cancer type they represent and others is confirmed. In breast cancer, for instance, our model identified well-known markers, such as GATA3 and ESR1. Finally, we extended the 1D-CNN model for the prediction of breast cancer subtypes and achieved an average accuracy of 88.42% among 5 subtypes. The codes can be found at https://github.com/chenlabgccri/CancerTypePrediction.

Conclusions
Here we present novel CNN designs for accurate and simultaneous cancer/normal and cancer types prediction based on gene expression profiles, and unique model interpretation scheme to elucidate biologically relevance of cancer marker genes after eliminating the effects of tissue-of-origin. The proposed model has light hyperparameters to be trained and thus can be easily adapted to facilitate cancer diagnosis in the future.
Prediction of circRNA-disease associations based on inductive matrix completion
Authors: Li Menglu , Liu Mengya , Bin Yannan , Xia Junfeng 
Published: April 2020

AbstractBackgroundCurrently, numerous studies indicate that circular RNA (circRNA) is associated with various human complex diseases. While identifying disease-related circRNAs in vivo is time- and labor-consuming, a feasible and effective computational method to predict circRNA-disease associations is worthy of more studies.ResultsHere, we present a new method called SIMCCDA (Speedup Inductive Matrix Completion for CircRNA-Disease Associations prediction) to predict circRNA-disease associations. Based on known circRNA-disease associations, circRNA sequence similarity, disease semantic similarity, and the computed Gaussian interaction profile kernel similarity, we used speedup inductive matrix completion to construct the model. The proposed SIMCCDA method obtains an area under ROC curve (AUC) of 0.8465 with leave-one-out cross validation in the dataset, which is obtained by the combination of the three databases (circRNA disease, circ2Disease and circR2Disease). Our method surpasses other state-of-art models in predicting circRNA-disease associations. Furthermore, we conducted case studies in breast cancer, stomach cancer and colorectal cancer for further performance evaluation.ConclusionAll the results show reliable prediction ability of SIMCCDA. We anticipate that SIMCCDA could be utilized to facilitate further developments in the field and follow-up investigations by biomedical researchers.