bluuebunny/crossref_metadata_2025_split huggingface dataset:
Barriers to Childhood Immunization in Sub-Saharan Africa: A Systematic Review
Authors: Bangura Joseph Benjamin , Xiao Shui-yuan , Qiu Dan , Ouyang Feiyun , Chen Lei 
Published: March 2020

Abstract
Background Immunization to prevent infectious diseases is a core strategy to improve childhood health as well as survival. It remains a challenge for some African countries to attain the required childhood immunization coverage. We aim at identifying individual barriers confronting parents/caretakers, providers, and health systems that hinder childhood immunization coverage in Sub-Saharan Africa. Method This systematic review searched PubMed/MEDLINE, Web of Science and EMBASE. We restricted to published articles in English that focused on childhood immunization barriers in Sub-Saharan Africa from January 1988 to February 2019. We excluded studies if: focused on barriers to immunization for children in other regions of the world, studied adult immunization barriers; studies not available on the university library, they were editorial, reports, reviews, supplement, and bulletins. Study designs included were cross-sectional, second-hand data analysis; and case control. Results Of the 2,538 items identified, 40 met inclusion criteria. Parents/caretakers were the most common subjects. Eight articles were of moderate and 32 were of high methodological quality. Seven studies analyzed secondary data; 30 used cross-sectional designs and three employed case control method. Twenty-five studies reported national immunization coverage of key vaccines for children under one, fifteen did not. When reported, national immunization coverages of childhood vaccines were reported to be low. Parents/caretaker’s barriers included lack of knowledge of immunization, distance to access point, financial deprivation, lack of partners support, and distrust in vaccines and immunization programs. Other associated factors for low vaccine rates included the number of off-springs, life style, migration and occupation. Barriers at health system level cited by healthcare providers included limited human resources and inadequate infrastructures to maintain the cold chain and adequate supply of vaccines. Conclusion In this review we identified more thoroughly the parents/caretakers’ barriers than those of providers and health systems. Factors that influenced decisions to get children vaccinated were mainly their gender, beliefs, socio-economic and socio-culture factors in the communities in which they live. Thus it is vital that immunization programs consider these barriers and address the people and societies in their communities across Sub-Saharan Africa.
A new approach for the load calculation of the most loaded rolling element for the rolling bearing with internal radial clearance - The case study
Authors: Tomović Radoslav 
Published: March 2020

Abstract
In this paper is presented a case study which has the goal to show the benefits of the application of a new approach for the calculation of load of the most loaded rolling element at the rolling bearing with the internal radial clearance. The calculation is based on the so-called load factors. By multiplication load factors with the value of the external radial load, the load which is transferred by the most loaded rolling element of the bearing is obtained. The case study is made for two types of bearings, the ball, and roller bearing. Obtained results were compared with the results obtained based on the calculation using some of the most commonly used methods so far. The analysis showed greater precision of the considered model with the same or much simpler application. For this reason, the proposed model is considered very suitable for practical application.
Delimiting cryptic morphological variation among human malaria vector species using convolutional neural networks
Authors: Couret Jannelle , Moreira Danilo C , Bernier Davin , Loberti Aria Mia , Dotson Ellen M , Alvarez Marco 
Published: March 2020

Abstract
Background Among mosquitoes that transmit human pathogens there are several species complexes, morphologically indistinguishable, distinct in their behavior and ecology, particularly as it relates to vectorial capacity. Morphological demarcation has remained largely intractable. Identification using molecular markers is the favored method in applied settings, prohibitively so, as the expense of such methods prevents the majority of mosquito surveillance programs to distinguish species within species complexes. Here, we apply computational methods in machine learning to delimit vector species within the Anopheles gambiae complex, which transmit human malaria and are notoriously difficult to distinguish based on morphology.Results We introduce a library of $1,709$ images collected from $15$ species colonies of mosquito vector species originating from five regions worldwide, with four sibling species from Africa that cannot be readily distinguished even amongst trained medical entomologists. Among them we include images of two strains of a single species, Anopheles gambiae s.s. . We varied storage method within a species to include two methods of storage, freshly frozen or dried, to test whether the same cage population could be distinguished by deep learning on this basis. We present a machine vision approach using Convolutional Neural Networks (CNN) with data augmentation that can achieve up to $97\%$ accuracy in distinguishing the genera, species, cryptic species, and between two strains of one species as well as storage method. We included three outgroup vector species from the Aedes and Culex genera known to transmit other human pathogens.Conclusion We demonstrate that deep learning models can delimit species with cryptic morphological variation, strains that are genetically differentiated but morphologically identical, and automate delineation of sex and storage method. These findings have broad reaching implications for the study of morphological variation and applications to the surveillance and study of human malaria.
Genes co-related with poor prognosis of patients with lung cancer via bioinformatical approaches
Authors: Shi Dai , Han Yeming , Wang Xin , Hou Guihua 
Published: March 2020

Abstract
Lung cancer is one of the most common malignant tumors with high mortality worldwide. Recently, researchers reported that molecular markers on lung cancer could be used as diagnostic and prognostic targets. However, these molecules were not ideal in specificity and high selectivity. Therefore, exploring more reliable biomarkers to improve the prognosis and clarify the underlying mechanism is urgently needed both for clinic and basic research. This study aimed to identify significant genes with poor prediction for lung cancer and their underlying mechanisms. Firstly, we used gene expression datasets available from GEO (Gene Expression Omnibus) database. There were 109 lung cancer samples and 27 normal samples in the selected datasets. First, DEGs (Different Expressed Gene set) of lung cancer and normal lung samples were screen out with GEO2R tool, and we displayed them by Venn diagram software and Heatmap. Secondly, we used DAVID (Database for Annotation, Visualization and Integrated Discovery) to analyze KEGG (Kyoto Encyclopedia of Gene and Genome) pathway and GO (Gene Ontology). Third, PPI (Protein-Protein Interaction) of these DEGs was conducted by Cytoscape with STRING (Search Tool for the Retrieval of Interacting Genes). Our results showed that the expression trends of 21 up-regulated genes and 116 down-regulated were similar in selected three datasets. Analyzed by MCODE (Molecular Complex Detection) plug-in, 11 up-regulated and 16 down-regulated genes were selected. To further verify gene expression differences, GEPIA (Gene Expression Profiling Interactive Analysis) was implemented and we found 26 of 27 genes were found differently expressed in lung cancer compared with normal lung tissues. Furthermore, Kaplan–Meier analysis was used and we found 23 of 26 genes for overall survival indicated much less survival time. At last, three genes, CDH5, CLDN5, PECAM1, were found to be significantly decreased in lung cancer tissue proved through re-analysis of DAVID, which mainly co-related with leukocyte trans-endothelial migration. In conclusion, three significant down-regulated deferentially expressed genes with poor prognosis on lung cancer were identified basing on integrated bioinformatical methods. These down-expressed genes may be as a potential prognosis targets for patients with lung cancer.
MicroRNA-1271-5p inhibits the tumorigenesis of ovarian cancer through targeting E2F5 and negatively regulates the mTOR signaling pathway
Authors: Li Qin , Shi Junyu , Xu Xiaoli 
Published: March 2020

Abstract
Background: MicroRNA-1271-5p (miR-1271-5p) has been reported to participate in the progression of many malignancies. However, the molecular mechanism of miR-1271-5p still remains vague in ovarian cancer (OC). Therefore, we explored the effect of miR-1271-5p in the development of OC in present study.Methods: We measured the miR-1271-5p expression via qRT-PCR assay. Western blot analysis was employed to examine protein expression. Then, the functional mechanism of miR-1271-5p was analyzed by MTT, Transwell and dual luciferase assays.Results: Downregulation of miR-1271-5p was found in OC, which can predict worse prognosis in OC patients. Further, miR-1271-5p directly targets E2F5 in OC. And miR-1271-5p restrained the proliferation, migration and invasion of OC cells via targeting E2F5. Additionally, upregulation of E2F5 was observed in OC, which predicted unfavorable prognosis in OC patients. Besides that, miR-1271-5p suppressed EMT and mTOR pathway in OC.Conclusion: MiR-1271-5p inhibited the tumorigenesis of OC through targeting E2F5 and negatively regulated the mTOR signaling pathway.
The Need for General Collective Intelligence in Addressing the Sustainable Development Goals
Authors: Williams Andy E 
Published: March 2020

Abstract
Background: This study explores the factors constraining group decision-making, where those factors might tend to restrict groups from selecting optimal solutions with regards to sustainability or sustainable development. This study also explores the factors constraining group decision-making from framing problems in the optimal way (choosing the optimal problem to solve), and how together these factors constraining groups from choosing the optimal problem to solve or the optimal solution to solve it with, might tend to bar groups from achieving optimal outcomes. To address the first set of constraints, collective intelligence algorithms aim to use the intelligence of crowds to select optimal solutions. To address the second set of constraints, General Collective Intelligence solutions, as defined in this paper, aim to further improve outcomes by selecting the optimal problem to solve.Results: In the absence of General Collective Intelligence fundamental economic forces are suggested to drive a continual increase in the alignment of group decision-making with the interests of decision-makers rather than with optimizing collective impact. And while sustainability and sustainable development might be achieved locally in the face of this misalignment, globally this misalignment is suggested to compete directly against that achievement. For this reason, maximizing collective outcomes such as impact on sustainability or sustainable development is suggested to require General Collective Intelligence in order to reliably increase the forces driving groups towards prioritizing collective impact until those forces are greater than the forces driving this misalignment. As a result, without General Collective Intelligence this misalignment of group decision-making in a direction other than optimal collective impact is suggested to be a hidden "bug" that may prevent sustainability and sustainable development from being reliably achievable globally through current sustainability or sustainable development programs.Conclusions: General Collective Intelligence is a pattern of biomimicry that potentially replicates the robust and stable multi-cellular cooperation nature has evolved over more than a billion years to enable cells in organisms to cooperate to sustainably achieve outcomes. Platforms organizing groups into such a General Collective Intelligence are suggested to be required in order for sustainability or the sustainable development goals to be reliably achievable globally.
The Impact of Internet use frequency on Non-suicidal self injurious behavior and Suicidal Ideation among Chinese Youth: An empirical study based on Gender perspective
Authors: Xin Moye , Yang Xueyan , Liu Kun , Boke Bilun Naz 
Published: March 2020

Abstract
Background: We attempted to find if there were gender differences in Non-suicidal self injurious (NSSI) behaviors and Suicidal ideation among Chinese youth, then analyze the impact of internet use frequency on these variables among youth of different genders.Methods: Based on the survey data from 6 high-schools and 4 universities in 4 cities in China, the gender difference in NSSI behaviors and Suicidal ideation and their related factors were analyzed in the study.Results: There was no significant gender difference in NSSI behaviors among Chinese youth, yet females reported significantly higher intensity of suicidal ideation compared to males; internet use frequency could explain the prevalence of NSSI behaviors and Suicidal ideation by gender, to some categories.Conclusions: The gender difference of NSSI engagement among Chinese youth was not statistically significant; while females had higher suicidal ideation than males; the overuse of social softwares was found to be a risk factor to both NSSI engagements and suicidal ideations for both genders; males would engage less NSSI behaviors when they spent more time on knowledge sharing softwares while might have more suicidal ideation when they spent too much time on gaming.
Socio-demographic influences on the prevalence of enteric helminth and protozoan infections in newly arrived migrant workers in Qatar
Authors: Younes Nadin , Behnke Jerzy M. , Ismail Ahmed , Abumadi Marawan 
Published: March 2020

Abstract
Background Intestinal parasitosis is a major concern for public health, especially in children from middle and low-income populations of tropical and subtropical areas. In this study, we explored the environmental and socio-demographic characteristics of immigrants in Doha Qatar, that might explain the persistence of the parasites that they harbor.Methodology This cross-sectional survey was conducted among 2,486 newly arrived expatriates and those who visited Qatar previously during the period 2012-2014. Through questionnaires and census data, we characterised the socio-demographics conditions at an individual, family and neighborhood levels.Results Combined protozoan infections were significantly associated with immigrants arriving in Doha for the first time. In univariate loglinear statistical models fitted in phase 1 of the analysis significant associations were observed between the prevalence of combined protozoan infections and personal and familial factors that included religion, the level of education of subjects, both parents’ educational levels and their jobs, and number of siblings. Furthermore, environmental effects on the prevalence of protozoan infections included the country of origin; the floor of the house, toilet type, household content index, provision of household water, arable farming background showed a strong association with protozoan infections as well. However in phase 2, multifactorial binary logistic generalized linear models focusing only on the significant effects identified in phase 1, showed that only five factors retained significance (age class, floor of house, household contents index, father’s education, and number of siblings). The only factors that had a significant effect on the prevalence of helminth infections were the subjects age class and the mother’s educational level.Conclusion The prevalence of intestinal protozoan parasites among immigrants to Qatar is clearly multifactorial in origin, determined by key familial relationships of subjects and also the environment in which the subjects lived prior to their arrival in Qatar. Moreover our results suggest that screening protocols for applicants for visas/work permits need to be revised giving more careful attention to the intestinal protozoan infections that potential immigrants may harbor.
Application of the APE2-CHN and RITE2-CHN scores for autoimmune epilepsy in Chinese patients: a retrospective study
Authors: Liu Wei-ping , Wang Mian , Zhang Chen , Zhao Charlie Weige , Xiao Bo , Zeng Chang 
Published: March 2020

Abstract
Background : Autoimmune epilepsy is recognized as a distinct entity of epilepsy with underestimated incidence. Our previous study reported that prompt diagnosis and early-initiated immunotherapy led to better outcome. We proposed to assess the feasibility and reasonability of the Antibody Prevalence in Chinese Patients with Epilepsy and Encephalopathy (APE 2 -CHN) and Response to Immunotherapy in Chinese Patients with Epilepsy and Encephalopathy (RITE 2 -CHN) scores in predicting Chinese patients with autoimmune epilepsy. Methods : We conducted a retrospective study of consecutive patients from Xiangya Hospital, Central South University (01/01/2017-02/28/2019) whose serum and/or cerebrospinal fluid (CSF) samples were examined for autoimmune encephalitis antibodies. Of these, patients with new-onset epilepsy or established epilepsy of unknown etiology were selected in our study. An APE 2 -CHN score was assigned to each patient and a RITE 2 -CHN score was calculated for each patient who received immunotherapy. Results : 191 patients meeting the diagnostic criteria for epilepsy were enrolled in our study. 36 were subsequently identified with specific etiologies. The rest of the 155 patients had an unknown etiology. Central nervous system-specific antibodies were detected in 76 (49.0%) of them, after excluding solely thyroid peroxidase antibody or glutamic acid decarboxylase antibody. N-methyl-D-aspartate receptor antibody (48.7%, 37/76) was the most common antibody specificity, followed by γ-aminobutyric acid type B receptor antibody (14.5%, 11/76). Certain clinical features such as new-onset epilepsy, autonomic dysfunction, viral prodrome, facio-brachial dystonic seizures/oral dyskinesia, inflammatory CSF profile, and mesial temporal magnetic resonance imaging abnormalities correlated with positive antibody results. Sensitivity and specificity of an APE 2 -CHN score ≥ 5 to predict the presence of specific neural auto-antibodies in our study were 85.5% and 58.9%, respectively. In the subset of patients who received immunotherapy (n = 112), sensitivity and specificity of a RITE 2 -CHN score ≥ 8 to predict favorable seizure outcome were 98.6% and 63.2% respectively. Conclusion : The APE 2 -CHN and RITE 2 -CHN scores were preferable tools in predicting positive serologic findings and prognosis of autoimmune epilepsy in Chinese patients with epilepsy.
Prognostic value of two novel genes SNX10 and PTGDS for cervical squamous cell carcinoma: an integrated bioinformatic analysis
Authors: Jiang Pinping , Cao Ying , Gao Feng , Sun Wei , Liu Jinhui , Xie Manxin , Fu Shilong 
Published: March 2020

Abstract
Background Cervical cancer (CC) is the primary cause of death in women. This study sought to investigate the therapeutic targets of CC. Methods We downloaded four gene expression profiles from GEO. The RRA method was used to integrate and screen DEGs between CC and normal samples. Functional analysis was performed by clusterprofiler. We built PPI network by STRING and selected hub modules via MCODE. CMap was used to find molecules with therapeutic potential for CC. We also validated hub genes in GEO datasets, GEPIA, immunohistochemistry. Cox regression analysis, TCGA methylation analysis and ONCOMINE were carried out. ROC curve analysis and GSEA were also done to dig out the significance of hub genes. Results Functional analysis revealed that DEGs were significantly enriched in binding, cell proliferation, transcriptional activity and cell cycle regulation. PPI network screened 30 prominent proteins, with CDK1 having the strongest association with CC. Cmap showed that apigenin, thioguanine and trichostatin A might be used to treat CC. Eight genes were screened out through GEPIA. Of them, only PTGDS and SNX10 have not been reported in CC related articles. The validation in GEO showed that PTGDS showed low expression in tumor tissues while SNX10 showed high expression in tumor tissues. Their expression profiles were consistent with the results in immunohistochemistry. They can distinguish CC and normal tissue and have good diagnostic efficiency. GSEA showed that the two genes were associated with the chemokine signaling pathway. TCGA methylation analysis showed that patients with low-expressed and hyper-methylated PTGDS had a bad prognosis than the patients with high-expressed and hypo-methylated PTGDS. Cox regression analysis showed that SNX10 and PTGDS were independent prognostic indicators for OS among CC patients. Conclusions PTGDS and SNX10 showed abnormal expression and methylation in CC. Both genes could be used to develop new target treatments for CC.
Physicochemical Characterization of Organic Honeys Harvested in the North West Algerian Area
Authors: Djelloul Zidane , Benaoula Sid-Ahmed , Daioui Abdeldjalil , El Mahi Mohammed Z.E. , Meddah Boumedien , Taleb Mourad 
Published: March 2020

Background:
Consumers have become aware that the industrial methods of honey production
have greatly affected the environment and product quality. Today, they want a reorientation of
these production modes to obtain healthy and natural organic products.

Objective:
This study is conducted to evaluate, for the first time in Algeria, the physicochemical
composition of organic honey’s harvest in the organic- North West Algerian area.

Methods:
Twenty-four samples of organic honey were harvested according to the organic beekeeping
rules, by selected volunteer beekeepers in organic regions and hives, and then, they were extracted
by the traditional method. Physicochemical parameters, such as pH, free acidity, density, electrical
conductivity, diastase activity, carbohydrates, hydroxyl methyl furfural (HMF), water content, ash,
color intensity and specific optical rotation were evaluated.

Results:
Mean values obtained for physicochemical parameters were: pH as 3-4.8, electrical conductivity
as 0.123-1.180 mS/cm, free acid as 8-30 mEq/kg, diastase activity as 8.02-40.54 (Shade units),
carbohydrates as 60.21-77.07%, sucrose as 1.04-8.97%, HMF quality as 4.67-27.63 mg/kg, water
content as 14.2-19.0%, ash as 0.09-0.86%, color intensity ABS450 as 288-1467 mAU, color intensity
(Pfund scale) as 0.30-137.34 mm and specific optical rotation at (-16.1)-(-3.8). The analysis indicated
that organic honey samples grown in selected sites of our local area are of good quality. All of the
obtained values were within the limits imposed by the present legislation (Codex Alimentarius).

Conclusion:
Analyzed honey samples are characterized as biological products of excellent quality
with interesting nutritional properties.
Excisional Haemorrhoidectomy: Where Are We?
Authors: Sena Giuseppe , Gallo Gaetano , Vescio Giuseppina , Carpino Antonio , Diaco Elia , Papandrea Matteo , Trompetto Mario , Sammarco Giuseppe 
Published: March 2020

:
Haemorrhoidal disease (HD) is defined as the symptomatic enlargement and/or distal displacement
of anal cushions and is one of the most frequent and ancient anorectal conditions. Bleeding,
during or after defecation, is the most common symptom. The color of the blood is typically
bright red covering the outer surface of the stools. The severity of HD is based on the degree of the
prolapse. There are several excisional surgery treatments. In this review, we describe the most common
techniques such as Milligan and Morgan, Parks, Ferguson and Whitehead technique.

:
Despite significant improvements in conservative treatments, excisional haemorrhoidectomy techniques
are the most effective treatment for III- and IV degree.