bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using autoencoders as a weight initialization method on deep neural networks for disease detection
Authors: Ferreira Mafalda Falcão , Camacho Rui , Teixeira Luís F. 
Published: August 2020

Abstract
Background
As of today, cancer is still one of the most prevalent and high-mortality diseases, summing more than 9 million deaths in 2018. This has motivated researchers to study the application of machine learning-based solutions for cancer detection to accelerate its diagnosis and help its prevention. Among several approaches, one is to automatically classify tumor samples through their gene expression analysis.

Methods
In this work, we aim to distinguish five different types of cancer through RNA-Seq datasets: thyroid, skin, stomach, breast, and lung. To do so, we have adopted a previously described methodology, with which we compare the performance of 3 different autoencoders (AEs) used as a deep neural network weight initialization technique. Our experiments consist in assessing two different approaches when training the classification model — fixing the weights after pre-training the AEs, or allowing fine-tuning of the entire network — and two different strategies for embedding the AEs into the classification network, namely by only importing the encoding layers, or by inserting the complete AE. We then study how varying the number of layers in the first strategy, the AEs latent vector dimension, and the imputation technique in the data preprocessing step impacts the network’s overall classification performance. Finally, with the goal of assessing how well does this pipeline generalize, we apply the same methodology to two additional datasets that include features extracted from images of malaria thin blood smears, and breast masses cell nuclei. We also discard the possibility of overfitting by using held-out test sets in the images datasets.

Results
The methodology attained good overall results for both RNA-Seq and image extracted data. We outperformed the established baseline for all the considered datasets, achieving an average F1 score of 99.03, 89.95, and 98.84 and an MCC of 0.99, 0.84, and 0.98, for the RNA-Seq (when detecting thyroid cancer), the Malaria, and the Wisconsin Breast Cancer data, respectively.

Conclusions
We observed that the approach of fine-tuning the weights of the top layers imported from the AE reached higher results, for all the presented experiences, and all the considered datasets. We outperformed all the previous reported results when comparing to the established baselines.
Extreme mobility of the world’s largest flying mammals creates key challenges for management and conservation
Authors: Welbergen Justin A. , Meade Jessica , Field Hume E. , Edson Daniel , McMichael Lee , Shoo Luke P. , Praszczalek Jenny , Smith Craig , Martin John M. 
Published: August 2020

AbstractBackgroundEffective conservation management of highly mobile species depends upon detailed knowledge of movements of individuals across their range; yet, data are rarely available at appropriate spatiotemporal scales. Flying-foxes (Pteropusspp.) are large bats that forage by night on floral resources and rest by day in arboreal roosts that may contain colonies of many thousands of individuals. They are the largest mammals capable of powered flight, and are highly mobile, which makes them key seed and pollen dispersers in forest ecosystems. However, their mobility also facilitates transmission of zoonotic diseases and brings them in conflict with humans, and so they require a precarious balancing of conservation and management concerns throughout their Old World range. Here, we analyze the Australia-wide movements of 201 satellite-tracked individuals, providing unprecedented detail on the inter-roost movements of three flying-fox species:Pteropus alecto,P.poliocephalus, andP.scapulatusacross jurisdictions over up to 5 years.ResultsIndividuals were estimated to travel long distances annually among a network of 755 roosts (P.alecto, 1427–1887 km;P.poliocephalus, 2268–2564 km; andP.scapulatus, 3782–6073 km), but with little uniformity among their directions of travel. This indicates that flying-fox populations are composed of extremely mobile individuals that move nomadically and at species-specific rates. Individuals of all three species exhibited very low fidelity to roosts locally, resulting in very high estimated daily colony turnover rates (P.alecto, 11.9 ± 1.3%;P.poliocephalus, 17.5 ± 1.3%; andP.scapulatus, 36.4 ± 6.5%). This indicates that flying-fox roosts form nodes in a vast continental network of highly dynamic “staging posts” through which extremely mobile individuals travel far and wide across their species ranges.ConclusionsThe extreme inter-roost mobility reported here demonstrates the extent of the ecological linkages that nomadic flying-foxes provide across Australia’s contemporary fragmented landscape, with profound implications for the ecosystem services and zoonotic dynamics of flying-fox populations. In addition, the extreme mobility means that impacts from local management actions can readily reverberate across jurisdictions throughout the species ranges; therefore, local management actions need to be assessed with reference to actions elsewhere and hence require national coordination. These findings underscore the need for sound understanding of animal movement dynamics to support evidence-based, transboundary conservation and management policy, tailored to the unique movement ecologies of species.
Seasonal influenza vaccination in Kenya: an economic evaluation using dynamic transmission modelling
Authors: Dawa Jeanette , Emukule Gideon O. , Barasa Edwine , Widdowson Marc Alain , Anzala Omu , van Leeuwen Edwin , Baguelin Marc , Chaves Sandra S. , Eggo Rosalind M. 
Published: August 2020

Abstract
Background
There is substantial burden of seasonal influenza in Kenya, which led the government to consider introducing a national influenza vaccination programme. Given the cost implications of a nationwide programme, local economic evaluation data are needed to inform policy on the design and benefits of influenza vaccination. We set out to estimate the cost-effectiveness of seasonal influenza vaccination in Kenya.

Methods
We fitted an age-stratified dynamic transmission model to active surveillance data from patients with influenza from 2010 to 2018. Using a societal perspective, we developed a decision tree cost-effectiveness model and estimated the incremental cost-effectiveness ratio (ICER) per disability-adjusted life year (DALY) averted for three vaccine target groups: children 6–23 months (strategy I), 2–5 years (strategy II) and 6–14 years (strategy III) with either the Southern Hemisphere influenza vaccine (Strategy A) or Northern Hemisphere vaccine (Strategy B) or both (Strategy C: twice yearly vaccination campaigns, or Strategy D: year-round vaccination campaigns). We assessed cost-effectiveness by calculating incremental net monetary benefits (INMB) using a willingness-to-pay (WTP) threshold of 1–51% of the annual gross domestic product per capita ($17–$872).

Results
The mean number of infections across all ages was 2–15 million per year. When vaccination was well timed to influenza activity, the annual mean ICER per DALY averted for vaccinating children 6–23 months ranged between $749 and $1385 for strategy IA, $442 and $1877 for strategy IB, $678 and $4106 for strategy IC and $1147 and $7933 for strategy ID. For children 2–5 years, it ranged between $945 and $1573 for strategy IIA, $563 and $1869 for strategy IIB, $662 and $4085 for strategy IIC, and $1169 and $7897 for strategy IID. For children 6–14 years, it ranged between $923 and $3116 for strategy IIIA, $1005 and $2223 for strategy IIIB, $883 and $4727 for strategy IIIC and $1467 and $6813 for strategy IIID. Overall, no vaccination strategy was cost-effective at the minimum ($17) and median ($445) WTP thresholds. Vaccinating children 6–23 months once a year had the highest mean INMB value at $872 (WTP threshold upper limit); however, this strategy had very low probability of the highest net benefit.

Conclusion
Vaccinating children 6–23 months once a year was the most favourable vaccination option; however, the strategy is unlikely to be cost-effective given the current WTP thresholds.
A robust 11-genes prognostic model can predict overall survival in bladder cancer patients based on five cohorts
Authors: Lin Jiaxing , Yang Jieping , Xu Xiao , Wang Yutao , Yu Meng , Zhu Yuyan 
Published: August 2020

Abstract
Background
Bladder cancer is the tenth most common cancer globally, but existing biomarkers and prognostic models are limited.

Method
In this study, we used four bladder cancer cohorts from The Cancer Genome Atlas and Gene Expression Omnibus databases to perform univariate Cox regression analysis to identify common prognostic genes. We used the least absolute shrinkage and selection operator regression to construct a prognostic Cox model. Kaplan–Meier analysis, receiver operating characteristic curve, and univariate/multivariate Cox analysis were used to evaluate the prognostic model. Finally, a co-expression network, CIBERSORT, and ESTIMATE algorithm were used to explore the mechanism related to the model.

Results
A total of 11 genes were identified from the four cohorts to construct the prognostic model, including eight risk genes (SERPINE2, PRR11, DSEL, DNM1, COMP, ELOVL4, RTKN, and MAPK12) and three protective genes (FABP6, C16orf74, and TNK1). The 11-genes model could stratify the risk of patients in all five cohorts, and the prognosis was worse in the group with a high-risk score. The area under the curve values of the five cohorts in the first year are all greater than 0.65. Furthermore, this model’s predictive ability is stronger than that of age, gender, grade, and T stage. Through the weighted co-expression network analysis, the gene module related to the model was found, and the key genes in this module were mainly enriched in the tumor microenvironment. B cell memory showed low infiltration in high-risk patients. Furthermore, in the case of low B cell memory infiltration and high-risk score, the prognosis of the patients was the worst.

Conclusion
The proposed 11-genes model is a promising biomarker for estimating overall survival in bladder cancer. This model can be used to stratify the risk of bladder cancer patients, which is beneficial to the realization of individualized treatment.
Risk factors for malaria infection prevalence and household vector density between mass distribution campaigns of long-lasting insecticidal nets in North-western Tanzania
Authors: Mosha Jacklin F. , Lukole Eliud , Charlwood J. Derek , Wright Alexandra , Rowland Mark , Bullock Olivia , Manjurano Alphaxard , Kisinza William , Mosha Franklin W. , Kleinschmidt Immo , Protopopoff Natacha 
Published: August 2020

Abstract
Background
Long-lasting insecticidal nets (LLINs) are the most widely deployed vector control intervention in sub-Saharan Africa to prevent malaria. Recent reports indicate selection of pyrethroid insecticide resistance is widespread in mosquito vectors. This paper explores risk factors associated with malaria infection prevalence and vector density between mass distribution campaigns, changes in net coverage, and loss of protection in an area of high pyrethroid resistance in Northwest Tanzania.

Methods
A cross sectional malaria survey of 3456 children was undertaken in 2014 in Muleba district, Kagera region west of Lake Victoria. Vector density was assessed using indoor light traps and outdoor tent traps. Anophelines were identified to species using PCR and tested for Plasmodium falciparum circumsporozoite protein. Logistic regression was used to identify household and environmental factors associated with malaria infection and regression binomial negative for vector density.

Results
LLIN use was 27.7%. Only 16.9% of households had sufficient nets to cover all sleeping places. Malaria infection was independently associated with access to LLINs (OR: 0.57; 95% CI 0.34–0.98). LLINs less than 2 years old were slightly more protective than older LLINs (53 vs 65% prevalence of infection); however, there was no evidence that LLINs in good condition (hole index < 65) were more protective than LLINs, which were more holed. Other risk factors for malaria infection were age, group, altitude and house construction quality. Independent risk factors for vector density were consistent with malaria outcomes and included altitude, wind, livestock, house quality, open eaves and LLIN usage. Indoor collections comprised 4.6% Anopheles funestus and 95.4% Anopheles gambiae of which 4.5% were Anopheles arabiensis and 93.5% were Anopheles gambiae sensu stricto.

Conclusion
Three years after the mass distribution campaign and despite top-ups, LLIN usage had declined considerably. While children living in households with access to LLINs were at lower risk of malaria, infection prevalence remained high even among users of LLINs in good condition. While effort should be made to maintain high coverage between campaigns, distribution of standard pyrethroid-only LLINs appears insufficient to prevent malaria transmission in this area of intense pyrethroid resistance.
A novel method of calculating stroke volume using point-of-care echocardiography
Authors: Aligholizadeh Ehson , Teeter William , Patel Rajan , Hu Peter , Fatima Syeda , Yang Shiming , Ramani Gautam , Safadi Sami , Olivieri Peter , Scalea Thomas , Murthi Sarah 
Published: August 2020

Abstract
Background
Point-of-care transthoracic echocardiography (POC-TTE) is essential in shock management, allowing for stroke volume (SV) and cardiac output (CO) estimation using left ventricular outflow tract diameter (LVOTD) and left ventricular velocity time integral (VTI). Since LVOTD is difficult to obtain and error-prone, the body surface area (BSA) or a modified BSA (mBSA) is sometimes used as a surrogate (LVOTDBSA, LVOTDmBSA). Currently, no models of LVOTD based on patient characteristics exist nor have BSA-based alternatives been validated.

Methods
Focused rapid echocardiographic evaluations (FREEs) performed in intensive care unit patients over a 3-year period were reviewed. The age, sex, height, and weight were recorded. Human expert measurement of LVOTD (LVOTDHEM) was performed. An epsilon-support vector regression was used to derive a computer model of the predicted LVOTD (LVOTDCM). Training, testing, and validation were completed. Pearson coefficient and Bland-Altman were used to assess correlation and agreement.

Results
Two hundred eighty-seven TTEs with ideal images of the LVOT were identified. LVOTDCM was the best method of SV measurement, with a correlation of 0.87. LVOTDmBSA and LVOTDBSA had correlations of 0.71 and 0.49 respectively. Root mean square error for LVOTDCM, LVOTDmBSA, and LVOTDBSA respectively were 13.3, 37.0, and 26.4. Bland-Altman for LVOTDCM demonstrated a bias of 5.2. LVOTDCM model was used in a separate validation set of 116 ideal images yielding a linear correlation of 0.83 between SVHEM and SVCM. Bland Altman analysis for SVCM had a bias of 2.3 with limits of agreement (LOAs) of − 24 and 29, a percent error (PE) of 34% and a root mean square error (RMSE) of 13.9.

Conclusions
A computer model may allow for SV and CO measurement when the LVOTD cannot be assessed. Further study is needed to assess the accuracy of the model in various patient populations and in comparison to the gold standard pulmonary artery catheter. The LVOTDCM is more accurate with less error compared to BSA-based methods, however there is still a percentage error of 33%. BSA should not be used as a surrogate measure of LVOTD. Once validated and improved this model may improve feasibility and allow hemodynamic monitoring via POC-TTE once it is validated.
Trends in the incidence of oral cancer in Saudi Arabia from 1994 to 2015
Authors: Alshehri Bandar M. 
Published: August 2020

AbstractBackgroundOral cancer is one of the most common non-communicable diseases worldwide. This paper presents an evaluation of the trends and geographical distributions of oral cancers in the Saudi Arabian population.MethodsData from Saudi Cancer Registry reports were used in this analysis, which assessed the period between 1994 and 2015. All cancer cases are recorded in these reports, as well as the age, gender, region and histological cancer sites for each patient. Age-standardised and age-specific incidence rates were calculated in these reports. For the purposes of this paper, only cancers of the lips, tongue and mouth were considered oral cancers.ResultsBetween 1994 and 2015, the Saudi Cancer Registry identified 172,424 cancer cases in total. Of these, 3184 were oral cancer. The mean age-standardised rate of oral cancer for the study period was 2.9 per 100,000 people; for females, it was 1.5, and for males, it was 1.4. The incidence of oral cancer varied by region, with Jazan displaying the highest age-standardised rate and Hail displaying the lowest. A positive correlation was observed between oral cancer incidence and age.ConclusionThe overall trend of the age-standardised rate for both sexes remained constant from 1994 to 2015. However, the oral cancer incidence in Saudi Arabia varies by region. Studying this variation in more detail will help to guide awareness programmes in the regions that are most in need.
SRSF1 regulates exosome microRNA enrichment in human cancer cells
Authors: Xu Yi-Fan , Xu Xiaohui , Gin Amy , Nshimiyimana Jean D. , Mooers Blaine H. M. , Caputi Massimo , Hannafon Bethany N. , Ding Wei-Qun 
Published: August 2020

Abstract
Background
Exosomes are extracellular vesicles containing a variety of biological molecules including microRNAs (miRNAs). We have recently demonstrated that certain miRNA species are selectively and highly enriched in pancreatic cancer exosomes with miR-1246 being the most abundant. Exosome miRNAs have been shown to mediate intercellular communication in the tumor microenvironment and promote cancer progression. Therefore, understanding how exosomes selectively enrich specific miRNAs to initiate exosome miRNA signaling in cancer cells is critical to advancing cancer exosome biology.

Results
The aim of this study was to identify RNA binding proteins responsible for selective enrichment of exosome miRNAs in cancer cells. A biotin-labeled miR-1246 probe was used to capture RNA binding proteins (RBPs) from PANC-1 cells. Among the RBPs identified through proteomic analysis, SRSF1, EIF3B and TIA1 were highly associated with the miR-1246 probe. RNA immunoprecipitation (RIP) and electrophoretic mobility shift assay (EMSA) confirmed the binding of SRSF1 to miR-1246. Lentivirus shRNA knockdown of SRSF1 in pancreatic cancer cells selectively reduced exosome miRNA enrichment whereas GFP-SRSF1 overexpression enhanced the enrichment as analyzed by next generation small RNA sequencing and qRT-PCR. miRNA sequence motif analysis identified a common motif shared by 36/45 of SRSF1-associated exosome miRNAs. EMSA confirmed that shared motif decoys inhibit the binding of SRSF1 to the miR-1246 sequence.

Conclusions
We conclude that SRSF1 mediates selective exosome miRNA enrichment in pancreatic cancer cells by binding to a commonly shared miRNA sequence motif.

Graphical abstract
Identification of a 4-lncRNA signature predicting prognosis of patients with non-small cell lung cancer: a multicenter study in China
Authors: Wang Rui-Qi , Long Xiao-Ran , Ge Chun-Lei , Zhang Mei-Yin , Huang Long , Zhou Ning-Ning , Hu Yi , Li Rui-Lei , Li Zhen , Chen Dong-Ni , Zhang Lan-Jun , Wen Zhe-Sheng , Mai Shi-Juan , Wang Hui-Yun 
Published: August 2020

Abstract
Background
Previous findings have indicated that the tumor, nodes, and metastases (TNM) staging system is not sufficient to accurately predict survival outcomes in patients with non-small lung carcinoma (NSCLC). Thus, this study aims to identify a long non-coding RNA (lncRNA) signature for predicting survival in patients with NSCLC and to provide additional prognostic information to TNM staging system.

Methods
Patients with NSCLC were recruited from a hospital and divided into a discovery cohort (n = 194) and validation cohort (n = 172), and detected using a custom lncRNA microarray. Another 73 NSCLC cases obtained from a different hospital (an independent validation cohort) were examined with qRT-PCR. Differentially expressed lncRNAs were determined with the Significance Analysis of Microarrays program, from which lncRNAs associated with survival were identified using Cox regression in the discovery cohort. These prognostic lncRNAs were employed to construct a prognostic signature with a risk-score method. Then, the utility of the prognostic signature was confirmed using the validation cohort and the independent cohort.

Results
In the discovery cohort, we identified 305 lncRNAs that were differentially expressed between the NSCLC tissues and matched, adjacent normal lung tissues, of which 15 are associated with survival; a 4-lncRNA prognostic signature was identified from the 15 survival lncRNAs, which was significantly correlated with survivals of NSCLC patients. This signature was further validated in the validation cohort and independent validation cohort. Moreover, multivariate Cox analysis demonstrates that the 4-lncRNA signature is an independent survival predictor. Then we established a new risk-score model by combining 4-lncRNA signature and TNM staging stage. The receiver operating characteristics (ROC) curve indicates that the prognostic value of the combined model is significantly higher than that of the TNM stage alone, in all the cohorts.

Conclusions
In this study, we identified a 4-lncRNA signature that may be a powerful prognosis biomarker and can provide additional survival information to the TNM staging system.
A case report of a novel compound heterozygous mutation in a Brazilian patient with deficiency of Interleukin-1 receptor antagonist (DIRA)
Authors: Mendonça Leonardo Oliveira , Grossi Alice , Caroli Francesco , de Oliveira Robson Aguiar , Kalil Jorge , Castro Fabio Fernandes Morato , Pontillo Alessandra , Ceccherini Isabella , Barros Myrthes Anna Maragna Toledo , Gattorno Marco 
Published: August 2020

Abstract
Background
Deficiency of the natural antagonist of interleukin-1 was first described in 2009 and so far 20 patients has been reported. In Brazil just two cases have been reported both carrying the same homozygous 15 bp deletion. Blocking interleukin-1 has changed rate survival for DIRA patients. The use of anakinra and rilonacept has been reported safe and efficient, whereas the selective blockade of interleukin-1 beta, using the monoclonal antibody canakinumab has been reported in a single case only.

Case presentation
Here we report a case of a 7 years old Brazilian boy that presented with recurrent episodes of systemic inflammation with severe disabling osteomyelitis with mild pustular skin rash. A Next Generation Sequencing gene panel allowed to detect two pathogenic mutations in the IL1RN gene, described in compound heterozygosity. Corticosteroids was effective in controlling inflammation and anti-IL1 beta blocker triggered disease flare. Complete clinical control could be achieved using IL-1 receptor antagonist.

Conclusions
DIRA is a severe, life threatening autoinflammatory condition with low numbers of patients described all over the world. The mutation p.Asp72_Ile76del in IL1RN is presented in all Brazilian DIRA patients already described and p.Q45* (rs1019766125) is a new mutation affecting the IL1RN gene. Following the pathogenesis of DIRA, blocking both subunits of interleukin one as well as antagonizing the receptor using anakinra or rilonacept seems to be effective. There is just one report using canakinumab for the treatment of DIRA and this is the first report of disease flare using this drug.